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About this book

Unifying Electrical Engineering and Electronics Engineering is based on the Proceedings of the 2012 International Conference on Electrical and Electronics Engineering (ICEE 2012). This book collects the peer reviewed papers presented at the conference. The aim of the conference is to unify the two areas of Electrical and Electronics Engineering. The book examines trends and techniques in the field as well as theories and applications. The editors have chosen to include the following topics; biotechnology, power engineering, superconductivity circuits, antennas technology, system architectures and telecommunication.

Table of Contents

Frontmatter

Power Generation, Transmission and Distribution (1)

Frontmatter

Methodology of Detection for Power Cable Insulation Defects Based on DC Voltage Withstand Test

The methodology of detecting the power cable insulation defect based on DC voltage withstand test is put forward in this chapter. The discriminate function related to transient voltage and current harmonic is constructed by transient voltage and current which are regarded as signal sources during the voltage adjusting process. Then, the minimum value of discriminate function is utilized to diagnose the existence and seriousness of insulation defects for the cable. In addition, this methodology can be used to test the existence of insulation damage for cable that has undergone DC voltage withstand test.

Yusheng Quan, Yu Zhou, Yuliang Wu, Zisen Ning, Jiacheng Xiong, Zhongyang Liu

Methodology of Forecasting the Developing Tendency of a GIS PD Based on the Fractal Dimension and Catastrophe Theory

In order to effectively predict the development of GIS PD, the fractal dimension and catastrophe theory is used in this chapter. A large number of experimental results described by a lot of literatures have confirmed the fractal feature of PD signal. So the fold model of the catastrophe theory can be used to analyze and monitor GIS PD, and a new GIS PD forecasting methodology is presented based on the fractal dimension and catastrophe theory in this chapter. GIS PD fractal dimension is used as variables to predict the GIS PD development in the methodology. The predicted voltage and time of the mutation points have a certain consistency after applying the folded model to the data of the dimension of different signals. Then the general statistical method is applied and the voltage of mutation point after removing the maximum and minimum can be got by analyzing the test data of GIS PD through this methodology. This chapter shows the effectiveness and feasibility of the methodology. It has a certain theoretical significance and practical value.

Yu-sheng Quan, Bo Yi, Yu-liang Wu, Bo Zhao, Shao-yu Liu, Liang Guo, Chun Deng

Calculation of Lightning Surge Distribution in Transformer Windings

In order to investigate the voltage distribution in transformer winding suffering from the lightning surge, a simulation model of 180-turn winding based on multiconductor transmission line theory is established and a new method for the calculation of voltage distribution is offered in this chapter. First, the finite element method calculates the electric parameters

R

,

L

,

C

, and

G

. Second, the voltage transfer functions are obtained by solving the MTL equations with all frequencies. Then the voltage transfer functions are fitted with rational functions by vector fitting. At last, the voltage response in transformer winding is shaped by the convolution between the voltage transfer functions and the excitation. The simulation (Ansoft and Matlab) and tested result confirm the validity of this proposed methodology. This research is of great significance for the safety running of transformer.

Jian He, Jiazhu Xu, Xilin Yan, Rong Jiang, Wusheng Lan

The Detecting Methodology of GIS Insulation Defects Based on the AC Withstand Voltage Test

The AC withstand voltage test is the most common method of GIS (Gas Insulated Switchgear) on-site withstand voltage tests. The AC withstand voltage test exists in a voltage step-up process, and the voltage waveform contains harmonic components. This chapter presents a new method to diagnose the insulation defects by applying the transient voltage and current generated in the voltage step-up process. This method takes the transient voltage and current as information sources and decomposes the transient voltage and current into a series of harmonic components which are taken as the sample data set. We put the sample data into the reference database and get the numerical values of correlation coefficient. When the value reaches its maximum, the sample data set has the highest similarity to one specific reference data set. According to the known insulation fault information of this specific reference data set, we can get more insulation fault information of this GIS than the AC withstand voltage test. This method can availably get the detailed local fault information of GIS and also detect whether the GIS has the insulation damage after the GIS pass through the AC withstand voltage test or not.

Yu-sheng Quan, Bo Yi, Yu-liang Wu, Bo Zhao, Shao-yu Liu, Liang Guo, Chun Deng

The Methodology of Detection for GIS Insulation Defects Based on Lightning Impulse Test

This chapter presents a new methodology of diagnosis on insulation defects of GIS based on lightning impulse test. This methodology turns part of the lightning impulse voltage and current decomposed into a series of harmonics and constructs a discriminant function which can diagnose insulation defects of GIS. According to the extreme value of the discriminant function, the diagnosis on insulation defects of GIS can be achieved. Whether the GIS passing lightning impulse withstand voltage test has insulation damage or not can be detected, which is quite instructive for insulation supervision of GIS.

Yusheng Quan, Bo Zhao, Yuliang Wu, Bo Yi, Zhida Sun, Shaoyu Liu, Liang Guo, Chun Deng

The Methodology of Detection for Power Cable Insulation Defects Based on AC Voltage Withstand Test

This chapter presents a new method of insulation defects detection for power cable based on AC withstand voltage test. This method considers transient voltage and current generated during boost process as signal sources to construct discriminant function related to the transient harmonic voltage and current. Then extreme value distribution of the discriminant function and frequency characteristic of total insulation resistance of cable insulation is calculated. Finally, the diagnosis of cable insulation defects and the assessment whether AC voltage test itself causes insulation damage or not are achieved. The proposed method makes full use of the valuable information provided by AC voltage withstand test. It improves the efficiency of AC voltage withstand test of power cable and is beneficial for the development of power cable detection technology.

Yusheng Quan, Lixin Ji, Bo Zhao, Zhenhong Liao, Shaoyu Liu, Liang Guo, Chun Deng

Moisture Real-Time Identification for Utility Boiler Based on Mechanism Analysis

In order to realize real-time measurement and identification of moisture as received basis in coal-fired power plants, a soft-sensing model is built in this chapter. By introducing mechanism of energy conversation inside the pulverizing system, the model can rationally discriminate between the high calorific value coal (HCV coal) and low calorific value coal (LCV coal) through one distributed computing software. For verification, mass data from field are adopted to show the accuracy and reliability of the model in practical application with coal fluctuation. Identification results show that the model can calculate multiple mills’ moisture and summarize to the weighted results through weighting coal feed quantity, and this method can be utilized to meet the need of power plant depending on proximate analysis. The soft-sensing model based on mechanism analysis can effectively measure the moisture of firing coal and thus the problem of safe operation of boiler will be solved.

Xiaobin Huang, Haoyuan Tang, Danyi Chi

Power Generation, Transmission and Distribution (2)

Frontmatter

Identification of Coherent Generator Groups Based on Stochastic Subspace Algorithm

With continuous expansion of power grid scale, the research of low-frequency oscillation has been the hot spot of power system stable operation. The load of power system possesses the characteristic of continuous variation in certain time span. This variation usually is random, and its effect can be simulated by the influence of ambient noise on system. The conventional analysis method, getting state matrix from system mathematic model, has encountered application limitation. Therefore, under the premise of ambient noise, this chapter adopted stochastic subspace method to identify coherence generator group which is in low-frequency oscillation. Based on state-space model and measured signal, by identifying system state matrix through stochastic subspace method and analyzing its eigenvalue, the method of identifying system coherence generators could be found. Through analyzing the system example of 3 generators and 9 nodes, and 16 generators and 68 nodes, the result indicated that the identification method this chapter adopted had higher identification accuracy and calculation efficiency.

Wei Xin, Yingyun Sun, Wei Wang, Ting Yu, Haotian Li, Hanzhi Zhang

Substation Topology Analysis Based on Improved Tracking Algorithm

The substation network topology analysis is an important part of power system network topology, which occupies a large number of total time of topology analysis. Improving the topology analysis efficiency is the key to ensure the rapidity of the power system network topology. The chapter first summarizes the main methods applied to the power system network topology analysis. Second, it proposes an improved tracking algorithm based on the analysis of two shortages in the existing tracking algorithm. Finally, the simulation results validate that the proposed algorithm for substation network topology analysis is easy to be practiced fleetly. There are only three steps for calculation when the network nodes are connected, which improves the speed of the network state estimation tremendously.

Shi Jianlei, Zhang Xuan, Zhao Qiang, Zhang Jinfang, Wang Zengping

Evaluation Methodology About the Effect of the Sophisticated Test of GIS

According to the related regulation, the sophisticated test of GIS is a necessary experiment project before conducting the AC voltage withstand test. But there is not an appropriate evaluation methodology to evaluate the effect of the sophisticated test. This chapter presents a method to evaluate the effect of the sophisticated test and diagnose the insulation defects. This method extracts the transient voltage and current which can be measured in the voltage step-up process as the information sources. As the voltage and current contain a large number of harmonic components which involve a great deal of information of the effect of the sophisticated test, they can generate the recognized criterion which is closely related to the harmonic components. The effect of the sophisticated test can be assessed, according to the extreme value distribution of the identification function. This methodology helps to improve the efficiency of the sophisticated test of GIS.

Yusheng Quan, Bo Zhao, Yuliang Wu, Bo Yi, Peng Ye, Shaoyu Liu, Liang Guo, Chun Deng

Harmonic Flux Distribution in Transformer Based on Harmonic-Balance Finite Element Method

To solve the problem of the existing methods which can only draw the total magnetic flux distribution, a new method for studying the harmonics of the magnetic flux distribution based on harmonic-balance finite element is proposed in this chapter. Firstly the theory of the harmonic-balance finite element method is introduced in this chapter. Secondly, a new type of converter transformer coupled with field–circuit mathematical model is established, and the corresponding 2D axis symmetric finite element model is provided. On that basis, the distribution of harmonic flux is obtained by writing programs using MATLAB software, with a deep analysis included. This method is an innovative approach and also makes up the shortcomings that finite element software cannot get the distribution of each harmonic magnetic flux which has important meanings in the design of the transformer and other electromagnetic equipments.

Qiang Hu, Derong Luo, Yong Wang

A Resonant Transformer with High Output Voltage Ratio

To solve the voltage breakdown of double resonant pulse transformer and improve the output voltage, a design method of triple resonant pulse transformer is proposed in this chapter. The relationship between the voltage of the high voltage winding, as well as that of the load capacitance, and the parameters is achieved by theoretical analysis of a triple resonant pulse transformer. According to the theoretical analysis, a series of parameters are designed and a circuit is simulated. The simulation results agree well with the theoretical analysis, which demonstrate that the relationship got by theoretical analysis is correct. The maximum voltage of the high voltage winding is only 0.36 times of the maximum output voltage, which improves the output voltage of a transformer and effectively solves the breakdown problem of the high voltage winding. The theoretical and simulation results show that the triple resonant pulse transformer is transformed with higher output voltage ratio.

Mingfei Wei, Fang Yang, Zhongxing Duan, Ying Wang

Field Tests and Optimization Operation Research of a 600 MW Power Plant WFGD

High efficiency and low cost are the two main goals of desulfurization system operation optimization. Some field tests were performed on a wet desulfurization system for a certain 600 MW coal-fired power unit. By changing the factors such as the absorber entrance concentration of SO

2

, absorber slurry pH value, the number of slurry circulating pumps, the regularity of desulfurization efficiency in different working conditions was studied. The results indicated that the desulfurization efficiency became higher when the entrance concentration of SO

2

was lower or the slurry ph value was higher. Running a pump at any load will increase the liquid–gas ratio so as the desulfurization efficiency. On the basis of field tests and the analysis of operation cost, the artificial intelligence methods were used in desulfurization system operation optimization. Firstly, BPNN models of desulfurization efficiency and booster fan current were built; secondly, an optimization model of desulfurization system operation cost was established to obtain the optimal parameters by the BBO algorithm, such as limestone slurry pH value, booster fan opening degree, liquid–gas ratio, etc. The optimal solution and data analysis showed that the proposed optimization control scheme in this chapter was effective to improve desulfurization efficiency and reduce operation cost.

Zongliang Qiao, Lei Zhang, Jie Li, Fengqi Si, Zhigao Xu

Power System Modeling and Simulation

Frontmatter

Simulation Models and Stability of PV Grid-Connected Power System Based on PSASP

In order to analyze the reliability and stability of PV grid-connected power system, a dynamic model of grid-connected PV power station was developed under PSASP environment. By using the User-Defined Model (UDM) of the PSASP, the photovoltaic array model, inverter model, DC–DC booster model, MPPT controller model and storage battery system model were designed, which were suitable for engineering application. Finally, based on a western isolated grid with PV power station connected, the effect of power grid trend by PV station in different output and different power factor, and the transient stability under the change of the sunshine intensity, and three-phase short-circuit fault were studied. Simulation analysis results indicated that the energy storage battery can maintain grid power balance and a constant voltage reduce the oscillation of the system after faults. The accuracy of model was proved through simulation analysis and the PV grid-connected power system was validated stable.

Siqing Sheng, Lei Hou, Xin Wu, Junsheng Li, Cuiyan Huang, Hui Fan

Delay-Dependent Small Signal Stability for Power System with Constant and Time-Varying Delays

Conventional small signal stability (SSS) model for power system is a kind of linear control system that uses Taylor’s formula at equilibrium point without considering time-delay influence. However, time delay, existing in transmission of data from the measurement location to a control center and communication of these data to control devices, would degrade SSS and even cause power system instability. This chapter investigates delay-dependent SSS by constructing a new SSS model for time-delay power system. A novel LMI-based SSS criterion is derived by adopting an improved Lyapunov–Krasovskii functional method. The upper bound of time delay, which ensures power system to maintain stability, is defined as the delay margin for SSS analysis. Case studies are carried out on synchronous-machine infinite-bus power system and multimachine power system. Satisfactory results demonstrate the influence of time delay on SSS and verify the correctness and effectiveness of the proposed model and its SSS criterion.

Bo Yang, Yuanzhang Sun

An Improved Dynamic Stability Analysis Method for Time-Delay Power System

The conventional power system dynamic stability model neglects the influence of wide area signal transmission delay and cannot describe dynamic stability mechanism of power system precisely. In order to analyze power system stability in the environment of wide area measurement system (WAMS), a new dynamic stability model of power system considering time-varying delay influence is constructed. Then a novel global asymptotic stability analysis method with less conservativeness for time-delay power system, which extends the small signal analysis method of power system by using an improved Lyapunov–Krasovskii functional, is also derived. Simulation tests verify the correctness of the proposed model and the feasibility of the proposed stability analysis method.

Bo Yang, Yuanzhang Sun

Identification of Excitation System under the Environment of Wide Area Measurement

In order to solve the identification of the two-input single-output excitation system model parameters, considering reactive power compensation coefficient based on the wide area measurement system (WAMS), an extended linear integral filter (LIF) method is used in this chapter. By extending the LIF method from the single-input model to the two-input model in excitation system, the global parameters’ identification for two-input single-output excitation system model is achieved. In order to verify the feasibility of the LIF method, an 8 machines and 36 buses power system is utilized. The results demonstrate that the excitation system parameters can be identified by using WAMS environment monitoring data. The LIF method can be used without the limitation of zero initial conditions. Meanwhile, the reactive power compensation coefficient is also obtained.

Yazhou Zhang, Yuan Liu, Meng Yao, Zhiqiang Li, Liang Zhao

Variable Parameter Equivalent Model for the Loadability of Key Transmission Line

In order to obtain the loadability of key transmission line under operation, a variable parameter equivalent model of power systems is proposed. This equivalent model was first inferred theoretically. And then, a practical method was given for forecasting equivalent parameters. At last, the feasibility and effectiveness of the equivalent model and the method were testified by a 9-node, 12-branch, and 5-machine test system. Empirical results show that the equation model can reflect the effect of parallel flow on the transmission line loadability in interconnected system. And the changes in the equivalent parameters can reflect the nonlinearity and time-varying properties of power systems. The model and method are feasible and effective in obtaining the loadability of transmission line.

Likai Liang, Xueshan Han, Yanling Wang

Load Modeling, Forecasting and Management

Frontmatter

A Hybrid Model for Short-Term Wind Speed Forecasting Based on Wavelet Analysis and RBF Neural Network

In order to forecast short-term wind speed more accurately to reduce the negative impact on the whole grid effectively, a hybrid model combining wavelet analysis and RBF neural network is proposed in this chapter. By introducing wavelet decomposition and single branch reconstruction, the original wind speed sequence can be decomposed to each frequency subsequence which has stronger regularity. Meanwhile, it can solve the problem of local optimization according to the ACF of each subsequence in the process of modeling. The case analysis shows that the hybrid model has higher forecasting precision than the single RBF one, which lays a good foundation for the short-term power forecasting.

Xiao-bin Huang, Pei-lin Mao, Xiao-peng Dong, Hao-yuan Tang

Z-BUS Loss Redistribution Based on Average Loss Coefficient

Z-BUS loss allocation naturally allocates transmission losses to each of the network buses and also reflects transmission lines parameters and the network topology. However, the losses assigned to the generation buses are too large, so it is necessary to adjust the calculated losses. In order to solve the problem of unreasonable allocation, a novel method using the average loss coefficient is proposed to redistribute the system losses to all load buses. The simulation results on IEEE 14-bus system illustrate the consistency of the new loss allocation method with some other methods and verify the feasibility and superiority of the new method.

Tiantian Lu, Wenying Liu, Xiaomin Zhang

Short-Term Load Forecasting Based on Fuzzy Clustering Analysis Similar Days

As to the short-term electric power load forecasting, its accuracy is affected by many uncertain influencing factors. To improve the forecasting accuracy, a novel method using Similar Days based on fuzzy clustering analysis is proposed in this chapter. Firstly it categorizes the weather factors as temperature, air pressure, wind speed, overcast day, rainy day, etc., and then together with week type and day type these factors form the influence items. According to the items above, fuzzy rules are applied to establish the mapping table to get the factors quantized. Next, the cluster technology is utilized to classify the content in the mapping table, and the similar days are chosen based on the clustering level, which is to reduce the numbers of samples and accelerate the speed of selection. Secondly, aiming to eliminating non-gaussian noise contained in the similar days’ power load, lifting wavelet transform is adopted to extract the low sequence components. Finally a Least Squares Support Vector Machine (LS-SVM), which is optimized by particle swarm optimization algorithm, is designed to predict the low-frequency part while mean square weighted method is used to predict the high-frequency part. The simulation results show that this fuzzy clustering similar days method is effective.

Long Yu, Yihui Zheng, Xin Wang, Lixue Li, Gang Yao, Hongtao Chen

Based IGARCH Error Correction of the PLS-SVR Short-Term Load Forecasting

Due to the complexity in the influencing factors of the prediction accuracy, using single forecasting method to improve the prediction accuracy is just impossible in practice. In this chapter, the partial least square (PLS)method was used to diminish the sample input data, which can improve the traditional Support Vector Regression (SVR) for short-time electricity load. Then, there is error sequence between the predictive value and the actual value, and the error sequence was considered as the forecasting data, which has the characteristics of obvious peak and fat tail. Next, Integrated Generalized Autoregressive Conditional Heteroskedasticity (IGARCH) model was used to build the electricity load error predicted model, and modify the original predictive value. Lastly, the forecasting method of this chapter based on PJM historical data was verified. The result shows that the mean absolute percentage error (MAPE) and mean square prediction error (MSPE) are 3.56 % and 1.75 %, respectively. Compared to other traditional predictive value, the model presented in this chapter has higher accuracy, which can be applied to predict the short-term electricity load.

Zhiqiang Chen, Shanlin Yang, Liqiang Hou

Short Term-Load Forecasting Based on Meteorological Correcting Grey Model

In order to improve the predict precision of GM(1,1) when it is applied to the short term load forecasting (STLF) problem, the meteorological information is taken into consideration. Firstly, an improved multi-strategy is used to organize the origin load data. Secondly, this chapter proposes meteorological analyzing and correcting algorithm to recognize the weather sensitive data and amend them. Then GM(1,1) is taken as the basic method to do the prediction. Finally, nearby trend extrapolation amending and similar-day replacing method is proposed to adjust the result and clear the mutation in it. Through the test, it is found that such method has a far more better precision than origin GM(1,1) when there is weather mutation in history days or predict days. The highest variety of accuracy can be up to 7 % and there is an average increase in predicting accuracy by almost 2 %. It can be concluded that such methods can not only take care of the social and climate affect but also considers the weakness of GM itself.

Run-hai Jiao, Chen-jun Su, Bi-ying Lin, Rui-fang Mo

Power System Planning, Control, Protection, Maintenance and Operation (1)

Frontmatter

Three-Phase Active Power Filter Based on Neural Network Model Reference Adaptive Control

Aiming to solve the problem of harmonics and low power factor in power system, a shunt three-phase active power filter (APF) based on neural network model reference adaptive control (NNMRAC) is designed to suppress the harmonics and improve power factor. The APF is based on a three-phase pulse width modulated (PWM) voltage source inverter (VSI) and corresponding control circuit. The DC capacitor voltage and the output current errors between reference model and APF are neural network’s inputs; neural network’s outputs are instruction currents, which are input into three hysteretic current controllers to generate the switching pulses of the VSI. Simulation results using MATLAB verify the effectiveness of the algorithm under different load currents and different power factor.

Li Hong, Qiao Lifang, Tian Mingxing

An Improved Differential Evolution Algorithm for Economic Dispatch with Value Point Effect

An improved differential evolution algorithm is proposed to solve the multi-dimensioned, non-convex, nonlinear economic dispatch model with value point effect. This algorithm takes advantages on improving population orthogonal initialization to make the initial solution distribution much more uniform, and then optimizing mutation operations to raise the ability of jumping out of local optimum, finally modifying equality constraints to guarantee the existence of solutions. Taking IEEE 30 nodes system for example in this chapter, the effectiveness and superiority of the improved differential evolution algorithm is demonstrated comparing with conventional algorithms.

Ya-Long Li, Wen-Ying Liu, Wei Zheng, Bo Du

The Methodology of Monitoring MOA Insulation Defects Based on Transient Voltage and Current

MOA is a major electrical equipment for limiting the over-voltage of the power system. Its reliability will directly influence the safe operation of the power system. This chapter presents a new online non-real-time monitoring method based on the transient voltage and current which result from the transient process of the power grid. This method applies the transient voltage and current which contains harmonic components to structuring the discriminant function. The discrimination function is a comprehensive criterion by comparing the sample data with the reference database. So this method can monitor and diagnose the insulation defects of MOA based on the maximum value of the discriminant function. At the same time, this method does not require added signal sources. It facilitates diagnosing the insulation defects and it is also very easy to be implemented. It contributes to the application and development of monitoring technology.

Yu-sheng Quan, Hui Wang, Yu-liang Wu, Bo Yi, Xiao-yang Chen

A 2-Span Mask Algorithm for Optimal Scheduling with Discontinuous Fuel Cost Function

Optimal scheduling with discontinuous cost functions and generating unit ramping rate is one of the main functions of power generation operation and control, because it reduces annual production cost by a large margin. This study presents a novel algorithm to solve the problem of combining unit commitment and economic dispatch of the thermal units while minimizing cost. The proposed algorithm divides all the units into five groups according to constraints and both boundary factors. Then, a searching window is developed to find potential combinations. A 2-span mask method is employed to obtain the optimal unit scheduling from these potential combinations. Moreover, a look backward rule and a direct compensation algorithm are applied to evaluate the actual solution. Finally, the two test cases are simulated and the results are analyzed through comparison with those obtained by using existing techniques. Simulation results demonstrate that the proposed method not only yields a better solution but also needs less calculating time than existing techniques.

SenNien Yu, KeRen Chen, HungJen Tsai

Single-Phase Ground Fault Detection of Small Current Grounding System Base on Wavelets Analysis

In order to improve the accuracy of line selection and reduce the possibility of single-phase ground fault in small current grounding system, this chapter solved two key problems including exploring the fault information of transient signals as much as possible and extracting the characteristic component of transient signals. This chapter proposed that the wavelet analysis theory is applied to the fault detection from the signal processing’s point of view and realized to select the fault line by extracting the characteristic component of transient signals through the wavelet analysis and the comparison of the modulus maxima. At last, the feasibility of the line selective method was verified through a typical system in MATLAB simulation.

Huanghuang Liu, Qianjin Liu

Dynamic Optimal CPS Control for Interconnected Power Systems Based on SARSA Algorithm

In order to get better control performances in a relatively dangerous environment, a novel dynamic optimal CPS control method for interconnected power systems using on-policy reinforcement learning (RL) algorithm-SARSA RL algorithm is introduced in this paper. This controller realizes online learning and optimization of the acceptance rate of CPS values by a reward function which is constructed by the system CPS values and a closed loop which is constructed by CPS control actions. Comparing with off-policy RL algorithm-

Q

-learning, SARSA is better in convergence ability and safer in selection of policy. It is shown in the simulation experiment that more effective CPS values can be obtained by the controller using SARSA RL algorithm than that by using

Q

-learning algorithm.

Tao Yu, Shuiping Zhang, Yidong Hong

Economic Operation Analysis of Multi-transformer Combinations

An optimization model related to economic operation of multiple sets of two-winding transformers is described. Under constraints of connection form and transformer load, all possible operation mode combinations are enumerated and realized by Visual Fortran 6.5. Under the same load condition, economy of alternative modes is compared, and the optimal operation mode of transformer c?ombination is chosen. With the change of load data considered, the optimal operation mode combinations corresponding to different load level are obtained, and economic operation regions corresponding to different operation mode combinations are selected. Table between operation mode combinations and economic operation regions is made out. Results of calculation example show that the presented model and approach are effective and practical.

Leilei Zhao, Hailian Song, Kunpeng Cheng, Penghui Sun

Reactive Power Optimization for Distribution Network Based on Chaos Guide Particle Swarm Optimization Algorithm with Gold Criterion

Voltage is an important aspect to measure the security of power system and reactive power can relatively exert great influence on the voltage level. So planning for reactive power is an important part of network planning. In this chapter a new algorithm called Gold Criterion Chaos Guide Particle Swarm Optimization (GCCGPSO) is presented in reactive power optimization for distribution. Firstly, a mathematical model of reactive power optimization for distribution network by capacitance is established. And the cost of system active power loss and investment in equipment is treated as the optimization objective. Meanwhile the node voltage and reactive power of generator is dealt with penalty function when they pass over the limitation. Then GCCGPSO is proposed. It adopts not only chaos algorithm with gold criterion to guarantee that the particles are not easy to fall into local optimum and search the same place, but also the Neighbor domain optimal item to promote the ability of choosing path. Finally, the result of the simulation shows that the algorithm is useful and has sound performance.

Ping Jiang, Xin Wang, Lixue Li, Yihui Zheng, Lidan Zhou, Zhongbao Zhang

Power System Planning, Control, Protection, Maintenance and Operation (2)

Frontmatter

Multi-objective Reactive Power Optimization and Multi-attribute Decision Making Considering the Risk of Voltage Collapse

In view of the impact on power system brought by voltage collapse, setting the minimum of the network loss and the minimum of the risk of voltage collapse as the objective functions, a multi-objective reactive power optimization model is established. By applying an improved differential evolution (DE) algorithm to this model, the Pareto optimal set is obtained. Then, technique for order preference by similarity to ideal solution (TOPSIS) method based on entropy weight is used to implement a multi-attribute decision making on the decision matrix composed of the Pareto optimal set, and an eclectic solution is selected to provide guidance for decision makers. The effectiveness of the proposed model and algorithm is verified on IEEE RTS79 test system.

Tian Xia, Jingyan Yang, Zhengzhong Zhang, Yuanyuan Yang, Yujia Li

Exploring Detection and Prevention of Harmonics in Electric Power System

In order to eliminate the harmonics and power a system effectively, the UPF and FPGA harmonic detection methods are used in this research to obtain the desired the amplitude-frequency and phase-frequency characteristics with changes of parameters, which avoid errors in traditional harmonic detection methods. A specific debugging plan is proposed after analyzing the synchronous sampling of the composite load conductance and the phase-lock loop. It shows that acquisition accuracy and acquisition speed can be improved significantly by equating the paralleled nonlinear load and filter with a resistive load and improving the integral of “moving window.” The analytical results also indicate that UPF and FPGA harmonic detection methods can overcome the limitation and drawback of traditional harmonic detection methods and can offer higher precision in harmonic detection.

Shibo Li, Xingying Chen

Selectivity of Zero-Sequence Current Backup Protection and Improvement Based on Wide Area Measurement System

For complicated power grid, the inverse time zero-sequence current protection is widely used, which can better solve the relay settings problem. In most cases, due to the natural distribution of the zero-sequence current, the selectivity of the protection can be guaranteed; however, in some cases it cannot. In this chapter, the selectivity of the zero-sequence current backup protection under the condition of internal ground fault on the double-circuit transmission lines was analyzed in detail. Studies showed that in this case the protection of the non-fault line of the double-circuit lines can operate correctly. However, when the system zero-sequence parameters and the location of the fault point met certain conditions, both the protections of the adjacent lines on the two sides of the double-circuit transmission lines had the possibility of unselective mal-operation. In order to solve this problem, improved method based on wide area measurement system was proposed. The use of multi-point zero-sequence voltage in this method can improve the selectivity and the speed of the backup protection. At last, PSCAD simulation was carried out to verify the correctness of the analysis.

Linlin Wu, Shaofeng Huang

Reactive Power Coordination During Emergency DC Power Support

Emergency DC power support can enhance the stability of a power system when one DC link is blocked. The lack of reactive power will cause the supporting DC link to be unable to reach its own set point, thus reducing the effect of emergency DC power support. Three methods were proposed to provide reactive power in this chapter. They are switching the filter of the blocked dc link step by step, installing SVC, and improving additional excitation control of the generators that are near the rectifier station. The result shows that the above three methods can increase the emergency DC power. The reserved filters can only affect the dc links which are near the blocked dc link and may cause overvoltage to the converter station of the blocked dc link; SVC and excitation control can reduce the number of the tripped generators. However, the excitation control shows better performance and also the overvoltage of the generators can be controlled within a reasonable range.

Min Li, Lijie Ding, Wen Hua, Zheng Xu

Gain-Scheduled LPV Control of a Single-Machine Infinite-Bus Power System

When the disturbances in power systems are large or a fault occurs, the performance based on linear approximation degrades severely, so the inherent nonlinearity can no longer be ignored. In order to solve such a problem, this chapter presents a new nonlinear control method for the transient stability control. First the nonlinear model can be transformed equivalently into an LPV system dependent on the rotor angle as the scheduling parameter. Then for the purpose of enhancing the transient stability and achieving good damping performance, a multi-objective control with both pole placement and minimization of property level (from the active power disturbance to the deviation of rotor angle) is applied. This model can be transformed to linear matrix inequality (LMI), thus can easily be solved by MATLAB tool. The simulation results approve that the new controller has obvious advantage in dynamic progresses compared to the traditional PSS controller.

Ying Shan, Xianrong Chang

A State Estimate Algorithm Based on Current Measurement for Offshore Oil Grid

State estimate is to use the redundancy of the real-time measurement system to improve data accuracy, automatically exclude the error message caused by random interference, and estimate or forecast the system state. It is also one of the core functions of the energy management systems. During the implementation of the energy management systems in the offshore oilfields power grid, we found that the number of measurements is not enough. The measurement is inaccurate and also there is too much current measurement in the protective relaying equipment. So this chapter introduces the node injection current as state vector, meanwhile simplifies the measurement equation of the system and enables the constraints linearization, which improves the convergence speed of the program. At the same time, the current in the protective relaying equipment is introduced into the measurements to ensure the system observability. At last, the examples demonstrate this program is also reliable while the system is in the split run.

Yingyun Sun, Haotian Li, Xin Wei, Sun Xiao, Xiaorong Xie

An Automatic Gain Control Digital Time-Division Integrator for NFM in ITER Utilizing Campbelling Technique

In order to achieve the real-time neutron flux monitoring in the presence of high-level mixed neutrons and background rays, a Field Programmable Gate Array (FPGA)-based Automatic Gain Control Digital Time-division Integrator (AGCDTI) is employed for Neutron Flux Monitor (NFM) in International Thermonuclear Experimental Reactor (ITER). With Campbelling technique and digital time-division integration, AGCDTI can obtain the time evolution of the Campbell integral value, which is proportional to the neutron flux. And an auto gain controller is applied to increase the dynamic range and quantization precision of the count rate. In addition, the high background rays-inhibiting ability of AGCDTI can also be implemented via the combination of a blank chamber and a fission chamber. The experimental results show that the temporal resolution of AGCDTI can reach 0.1 ms, and its wide gain range is from −11.5 to 20 dB with the gain step being approximately 0.49 dB. Furthermore, AGCDTI can provide a wide linear dynamic range of count rate from 5×10

3

to 1.22×10

9

cps through the automatic gain control. These excellent performances demonstrate that AGCDTI can realize the anticipated goals of NFM perfectly. It will not only help to control, evaluate, and optimize plasma performance in ITER but also have potential applications wherever high-level mixed radiation fields need to be investigated, such as nuclear power stations, medical applications, and particle accelerators, and so on.

Li Shiping, Xu Xiufeng, Cao Hongrui, Yin Zejie, Yuan Guoliang, Yang Qingwei

The Similarity Between the Derivative of LEMP and Its Approximate Result for Oblique Channel in Near Area

In order to protect sensitive electronic components and electrical equipment against the influence of lightning electromagnetic pulse (LEMP) field in near area, it is necessary to determine the waveform of the lightning electromagnetic field. By using the dipole method to solve Maxwell’s equations, the analytical expressions of lightning electromagnetic fields which is generated by oblique discharge channel are presented. According to the TL model, the general approximate derivative expressions of lightning electromagnetic field are derived and the waveforms of the exact expressions as well as approximate expressions are compared in near area. The results showed that the electromagnetic field derivative waveforms of the approximate results are essentially coincident with that of the accurate results within 100 m and the deviation between the accurate result, and the approximate result increased with the increasing of the horizontal distance; the deviation between the approximate result and the exact result of magnetic field is larger than that of electric field within the same distance. From above analyses it can be concluded that there is an approximation between the lightning electromagnetic field and channel base current and from then on we can get lightning electromagnetic field more effectively.

Wang Xiaojia, Chen Yazhou, Wan Haojiang, Wang Lin

STATCOMS and HVDC

Frontmatter

STATCOM-Based Ice-Melting System of the Catenary System

In order to solve the frozen problem of the catenary system for electrified railway that occurs in the extreme weather in winter and will affect the pantograph’s taking the normal current and cause damages to the pantograph, a STATCOM-based traction network ice-melting (TNIM) system for electrified railway is proposed. By installing STATCOM devices in both the head and the end of the traction network, these devices can provide ice-melting current in cold weather and provide compensation current in normal weather. Simulations show that the ice-melting current and the compensation current will be gained by different control strategies, and the calculation method of ice-melting current and the single-phase STATCOM control strategy are all provided. The STATCOM-based TNIM system can not only provide ice-melting current for traction network but also realize reactive power compensation and the voltage compensation at the end of traction network. In addition, it can protect the catenary and guarantee safe, reliable, and punctual running of the locomotive.

Li-ping Zhao, Fei Chang, Xiangyu Wen, Zhijian Wu

Three-Phase Four-Wire STATCOM Control Method Based on Neural Network PI Controller

In order to solve the neutral-point imbalance problem and to improve the control precision of three-phase four-wire STATCOM, this chapter focused on the three-phase four-wire STATCOM control method based on neural network PI controller. First by analysis of the voltage imbalance problem of the split capacitors in three-phase four-wire STATCOM, a neutral-point balance control method based on the zero-sequence current is proposed. Then in order to improve the control precision, the neural network PI controller is introduced into three-phase four-wire STATCOM. Finally, the neutral-point balance control and neural network PI controller are combined together to get the neural network triple close-loop control method. Simulation result illustrates that the proposed control method is capable of neutral-point balancing control in three-phase four-wire STATCOM and the control precision is higher than that of the conventional control method.

Jinghui Liu, Yihui Zheng, Gang Yao, Lidan Zhou, Xin Wang, Junliang Li

Direct Output Voltage Control Strategy for STATCOM Based on Multi-model and Neural Network PI Controller

Aiming to deal with the voltage control problems and the limitations of the conventional PI controller in the Static Synchronous Compensator (STATCOM), a direct output voltage control strategy based on multi-model and neural network PI controller is proposed. This control scheme applied the multi-model and neural network technology to the PI controller to meet the accuracy and speed of the voltage control under different impact loads. Meanwhile, the neural network technology was used to tune the PI controller parameter values according to an optimal control law, which can meet the requirements of full range working conditions and optimality. Simulation experiments show that compared to the traditional PI controller, PI controller based on multi-model and neural network is proved to be better capable of adapting to the change of voltage with a higher compensating precision.

Chen Zhou, Yihui Zheng, Xin Wang, Lixue Li, Gang Yao, Ning Xie

Relationship Between Electric Field and Contamination Deposited Characteristics of ±800 kV UHV DC Insulators at High Altitudes

In order to study the relationship between the contaminations deposited characteristics and the electric field of the ultra-high-voltage (UHV) DC insulators, in the long-term live examination field for UHV DC equipments, an important part of National Engineering Laboratory for UHV Engineering Technology (Kunming), the contamination deposited characteristics of UHV DC insulators were researched, which run under a voltage level of −800 kV. There were three kinds of insulator strings selected for contamination measurement, and then, the electric field along the insulator strings has been analyzed by finite element software ElecNet. In the view of the electric field, the contamination distribution along the insulator string has been explained. The results indicate that there was a close relationship between the contaminations deposited characterizes and the voltage distribution, especially, the voltage and the ESDD (NSDD) have the same trend under the test condition. This work can give some important references about external insulation of UHV DC transmission project in China’s high-altitude areas.

Fangcheng Lü, Chunxu Qin, Yunpeng Liu, Wenyi Guo

Analysis and Simulation of Cascade STATCOM Based on PAM Inverter

In order to achieve similar harmonic elimination effect as Pulse Width Modulation (PWM) method at a lower switching frequency and solve the problem of DC capacitor voltage unbalance, the Pulse Amplitude Modulation (PAM) method and the method of pulse exchanging circularly are proposed in this chapter. By solving the optimal objective function, the angles of switching point can be worked out. It makes the low harmonic performance and the total output voltage optimal. The pulse generators rotate each fundamental frequency cycle time in the pulse distribution, and 10 fundamental cycles (200 ms) are needed to complete one cycle pulse rotation mechanism, which effectively improves the condition of the capacitor voltage difference. Then a neural network PI controller is designed to tune the parameters of the PI controller timely. The results of simulation show the correctness of the proposed method. It can adjust the changes through the simulation.

Longdi Sui, Yihui Zheng, Xin Wang, Lixue Li, Gang Yao, Xinyuan Liang

Power Line Communications and Power Flow Analysis

Frontmatter

Relay-Enabled Hybrid Wireless and Powerline Communication Access Network for Smart Power Grid

As the main approach to realize intelligent electric distribution, the power line communication (PLC) technology still faces the problem of topology complexity in this field. In this article, a Hybrid Wireless–PLC-Based Relay Scheme in Access Network is proposed for smart power grid, which combines advantages of both PLC and wireless technologies to solve the problem of topology complexity. Experimental results showed that this mechanism with routing approach had better performance.

Huifeng Bai, Mingwei Li, Dongshan Wang, Licheng Wang, Ting Zhao

The Impact of SRS Effect and Attenuation on Transfer Power in DWDM System

In order to analyze Stimulated Raman Scattering (SRS) effect separately, the methods of difference and quotient are proposed in this chapter, which ignored interference factors effectively. By introducing transfer difference and relative quotient measure, the power of dense channels’ transferring with the transmission distance was discussed. For illustration, the influences on the shortest wavelength channel were studied by using MATLAB simulation among different channel spacing, channel numbers, and input power. The results showed that input power became one of the most sensitive factors to the SRS effect when distance was extending and the limitation of quotient value of transferring power was a constant. The way of difference and quotient can solve the conflicts of variable interference from inherent properties of optical fiber, such as Attenuation, and thus the above analysis has important significance for the follow-up Nonlinear study of optical communications.

Tengyun Zhao, Yu Liu, Wenxiu Zheng

An Algorithm for Power Flow Control Based on the Generation Adjustment

Based on the physical characteristics of power network, this chapter summarizes the key factor, which affects the power flow distribution—the generator’s actual operating mode. And this chapter establishes a control model for power flow, which according to the operation requirements can determine the operations that generator requires, and the power distribution of the network. This solution solves the control model by means of combining the advantages of the sensitivity algorithm and the modern optimization methods, simultaneous equations, and the introduction of an appropriate amount of the unit’s operating parameters. At the same time, the power distribution in the system and the output of the unit, which are calculated by the model, are more accurate and reasonable. At last, this chapter shows the validity, accuracy, and reasonableness of the proposed model and the solution through the example of IEEE 5 and 30 bus system.

Liulin Yang, Cong Huang

Flexible Power Flow Algorithm of AC–DC Power System

In order to further improve the computational efficiency of existing power flow algorithm, a model of flexible power flow of AC–DC power system was proposed based on existing research achievements of flexible power flow. The active and reactive powers were decoupled and then the correction equations of P-Q decoupled flexible power flow of AC–DC power system were deduced. Flexible power flow algorithm of AC–DC power system took account of the impact of DC power system for flexible power flow calculation. The computational results contained the node voltages, the system frequency, and the values of the extension variables which were introduced in DC power system. The proposed flexible power flow algorithm can enrich and improve the calculation function of the original flexible power flow algorithm of AC power system. The computational results validated the effectiveness of the model and algorithm proposed in this chapter.

Xiaopeng Tian, Ming Fu

Reliability, Diagnostics and Prognostics

Frontmatter

Development of High-Voltage Discharge Fault Detection System

A high-voltage discharge fault detection system was developed based on ultraviolet (UV) image processing technology. By making use of image processing theory, the interference of noises in ultraviolet images was effectively eliminated. In addition, a fault state recognition method was established and tested for the high-voltage discharge fault detection with the data from the developed system. And an approach based on RBF artificial neural network theory is proposed. According to the results simulated by MATLAB program, the developed system as well as the fault state recognition method could identify device faults and operation conditions accurately,and also they match well. Therefore, the developed high-voltage discharge fault detection system using UV image processing technology has potential for practical use.

Bohao Tao, Lixin Ma, Liping Zhang, Yang Bai, Bo Hu

Swing Blocking Criterion Based on Voltage Frequency Characteristics

Traditional swing blocking criterion can prevent malfunction of distance protection during power swings, but at the same time can reduce the performance of distance protection. In order to solve this problem, theoretical analysis about voltage frequency characteristics during power swings is carried out in detail. Studies show that compared with the voltage frequencies on both sides of the non-swing center, the voltage frequencies on both sides of the swing center has distinct characteristics. When the difference between the voltage frequencies on both sides of the swing center increases, both of the voltage frequencies accelerate the change; on the contrary, when the voltage difference decreases, both of the voltage frequencies decelerate the change and the voltage frequencies on both sides of the swing center have no intersection. Thus the chapter proposes a new swing blocking criterion based on voltage frequency characteristics. This criterion can identify the location of the swing center and detect three-phase short-circuit fault occurring on the swing center line shortly. BPA simulation is carried out to verify the correctness of the method.

Linlin Wu, Shaofeng Huang

A Reliability Evaluation Method of Generation and Transmission Systems Based on Sequential Monte-Carlo Simulation

As the reliability evaluation of multiple faults in generation and transmission systems could easily lead to the “curse of dimensionality,” a reliability evaluation method of generation and transmission systems based on sequential Monte-Carlo simulation is put forward in this chapter. The thought of this method is “space for time” and it accelerates reliability evaluation process by storing system states and stating evaluation results. Besides, this method transforms multiple faults to single fault, which achieves both the goals of an accurate evaluation of multiple faults and small extra computation. This chapter gives the flowchart of this method and verifies its advantages of reliability evaluation in large-scale generation and transmission systems by considering the example of IEEE-RTS79.

Yaohao Wu, Wenying Liu, Chen Liang

Fault Diagnosis of Micro-grid Based on Petri Net

Micro-grid is the next generation of distribution system, which could make full use of clean energy (Jacobs and Bean, Power Syst Prot Control 38(14):5–11, 2010). This chapter analyzes the characteristics of Micro-grid and describes the typical form of Micro-grid. Considering the requirements of protection and fault diagnosis in Micro-grid, combined with object-oriented thinking and database theory, the chapter puts forward fault diagnosis model of Micro-grid based on high-level Petri net. The model also adds time stamps to the elements to achieve the priority of diagnostic logic. Taking into account that the protection may fail to operate and the loss may happen in information transmission, fuzzy theory is introduced in fault diagnosis model to enhance the robustness of the fault diagnosis model. At last, according to the example and verification, it can be proved that fault diagnosis of Micro-grid based on advanced Petri net is valid.

Hongxia Wu, Guoming Yang, Ailing Zhang, Honglin Wu

Bearing Fault Diagnosis Based on Cyclic Statistics Method

In order to reduce the influences caused by background noise and interference and exact the fault characteristic frequency, the basic theory of second-order cyclic statistics is studied in this chapter. The excellent demodulation ability of second-order cyclic statistics is proved by simulative analysis. In the bench test, the fault characteristics frequency of bearing outer raceway and its harmonic can be recognized clearly in frequency domain through the spectral correlation density when cyclic frequency is zero. The result has higher signal to noise ratio (SNR). Compared with the traditional spectrum analytical methods, the impacts of background noise and interference are furthest reduced by cyclic statistics and the fault characteristic frequency of bearing is identified accurately.

Mian-hao Qiu, Fu-Zhou Feng, Hua Cong

Smart/Micro Grid Distribution

Frontmatter

The Realization of the Distribution Network Self-healing Function and Dynamic Evaluation of Estimation Methods

As the immune system of Intelligent Grid, “self-healing” is the most important feature of intelligent grid. This chapter compares connection methods of distribution network with those of several other cities and discusses how the distribution network implement is the “self-healing” feature of intelligent grid. As there has been no evaluation criterion on the network “self-healing” function yet, this chapter proposes a dynamic assessment method for the network self-healing function, which is based on the improved static network connectivity analysis method. This new method could accurately determine whether the distribution network fails to achieve self-healing and it also can be used as a testing method for the ability of re-prevention.

Zhang Xuan, Wang Zengping, Shi Jianlei, Li Xiang

Combination of Heat and Power Used in the Distributed Energy System

In order to offer residents daily life energy consumption (power and heat) and to enhance the efficiency of energy utilization in HeTian area in Xinjiang Province, a distributed energy system with the combination of heat and power is built in this chapter. By inducing three mathematical models (photovoltaic modules, electrolyzer, and fuel cell) and an energy system operation strategy, the electricity and heat load of the residents can be showed. According to the analysis of the result, whether this distributed energy system can provide enough energy for the 40 families depends on the surface area of the PV panels. Residents in HeTian area can use this combination of heat and power (CHP) system to supply the hybrid electric-thermal load.

Shi-fu Wang, Chun-hua Li, Jing-wei Zhao, Xian-ming Zhang, Quan Wang, Qiang Xiao

Microgrid Multi-objective Economic Operation Optimization Considering Reactive Power

In order to solve the multi-objective energy optimization problem with conflicting sub-objectives, fuzzy optimization theory is used in this chapter. The optimization model of multi-objective economic-operated combined heat and power (CHP) microgrid system considering heating income is established in this chapter. The microsources can provide both active and reactive power in the model. A typical microgrid consists of a wind turbine, a photovoltaic, a storage battery, a microturbine, a fuel cell, and heating and electric loads. The maximum fuzzy satisfaction degree method is adopted to transform the multi-objective optimization problem into a nonlinear single-objective optimum problem. The improved genetic algorithm is used to optimize microsources’ active and reactive output and the satisfaction degree of multi-objective optimization for grid-connected mode considering spot price. And the single-objective and multi-objective optimal values are comparatively analyzed. Simulation results show that multi-objective model is more precise than single-objective model in reflecting the actual operation characteristics of microgrid and the better environmental benefits can be reached at operation cost as low as possible in this model. So the validity of the proposed model and algorithm is proved.

Jie Chen, Xiu Yang, Lan Zhu, Meixia Zhang

State Estimation of the Micro-grid

For the goal of actual needs of power companies, this chapter develops a state estimation procedure of the micro-grid, using branch currents as state variables, so that the measurement functions of nodes and branches can be expressed by these state variables. Micro-powers can be processed as different node types in grid or isolated operation according to different control methods that can also provide various real-time measurements in the state estimation. In this chapter, an IEEE-33 nodes micro-grid is adopted as an example. The performance of the state estimation program is tested by contrasting the estimated values and true values given by the power flow calculation. The result proves that the estimated values are close to true values and the method is feasible.

Jinling Lu, Guodong Zhu, Yuyang Miao

A Multi-Agent Energy Coordination Control Strategy in Microgrid Island Mode

In order to efficiently dispatch power between generators and loads in microgrid within a noncooperative environment, this chapter presents an energy coordination control strategy based on multi-agent system (multi-agent system, MAS) under the island mode. Considering distributed generation interests, each agent with its own mechanism for decision making interacts and collaborates to achieve the overall goal of the system. Mentality of MAS framework designing, typical distributed generation agent and load agent models, energy coordination control strategy based on priority list, and the dominant agent algorithm are proposed. An example of a particular microgrid is utilized to discuss the agent behavior characteristics and the reliability of energy coordination strategy. Results verify that the proposed method can dispatch energy flexibly in real time and ensure stable and economical operation of microgrid.

Ming Ding, Kui Luo

The Auto-tuning of ASC and Fault Online Selection Device in Intelligent Substation

In this chapter, the characteristic of single-phase earth fault in the 10kV isolated neutral distribution network is studied. The application of the auto-tuning of arc suppression coil (ASC) and fault line selection device in a 110kV intelligent substation is introduced. The application in field shows that the auto-tuning of ASC and fault line selection device can measure system reactive power and adjust the tap of ASC to the proper position in normal operation state to ensure the safe and reliable operation of the system. And when the single-phase earth fault occurs, the fault line can be selected correctly and the line-selection success rate is up to 100%. The applications of this device can reduce the workload of the substation maintenance, shorten the accident processing time, and improve the level of automation and intelligent substation and operation personnel’s working efficiency.

Haibo Bu, Zhihong Zhang, Fazhang Li, Yanjun Li

Soft Switching and Multilevel Converters

Frontmatter

A Novel Soft-Switching Converter with Passive Auxiliary Resonant Commutation

A novel soft-switching converter with passive auxiliary resonant commutation is presented in this chapter. Soft-switching of the switch can be achieved by using passive auxiliary resonant network. It is very attractive for high power application where IGBT (insulted gate bipolar transistor) is predominantly used as the power switch. Its operation principle is analyzed through its application to the boost converter. The condition of soft switching and the design considerations is analyzed in detail. The novel soft-switching cell can be also used in other basic dc-dc converter. A 5kW, 20kHz prototype which uses IGBT has been made. The effectiveness of the proposed converter is confirmed by the simulation and experimental results.

Enhui Chu, Xutong Hou, Mengyang Wu, Shijie Yan, Mutsuo Nakaoka

Soft-Switching Technology of Bidirectional DC-DC Converter for High-Power Flywheel Energy Storage System

High-power flywheel energy storage system (FESS) is widely considered as a potentially major energy storage system in the future. In order to improve the practicality and reduce high-power loss brought by high-power FESS in charging and discharging operation modes, a quasi-resonant zero voltage switching (QRZVS) bidirectional DC-DC converter for high-power FESS is proposed in this chapter. Energy transfers in two directions with switches works alternately, and the QRZVS circuit with only

$$ {L_\mathrm{{r}}}-{C_\mathrm{{r}}} $$

passive components suppresses the turn-on and turn-off loss during wide range of duty-cycle of IGBT. This DC-DC converter with two-quadrant operation has the characteristics of simple structure and low switching loss, realizing the ability of quick charge and discharge and reducing the electromagnetic interference level of the system. Testing results verified the advantages of the converter.

Zhang Weiya, Li Yongli

A Fast SVPWM Algorithm for Five-Level Inverter Considering Over-Modulation Region

In order to simplify vectors selection and function time calculation, increase the DC bus voltage utilization ratio and expand the operation range of induction machines; this chapter proposes a new SVPWM algorithm and the control strategy in the over-modulation section. In the new algorithm the coordinate transformation is not necessary. DSP2335 and FPGA are adopted in the experiment and the results prove the feasibility of the algorithm even in the over-modulation region.

Yang Tai-peng

Loss Calculation of NPC Three-Level Converter in Permanent Magnet Direct-Drive Wind Power Generation System

Permanent magnet synchronous generator with a full-scale converter is more attractive for large wind turbines at MW levels because of its low maintenance, reduced gearbox, high efficiency and power density, better low voltage ride through capability. As the increasing of converter’s capability, the device’s losses expand significantly, which directly affects the thermal design of the converters. In this chapter, a practical loss calculation method is derived based on the analysis of the conduction and switching principles of the NPC three-level converter at both generator and grid sides. Using thermal resistance equivalent circuit, the device’s junction temperatures are acquired. The infrared thermal imager is used to capture the temperature distribution of the converters and the thermal characteristics are analyzed in detail.

Wei Jing, Guojun Tan, Zongbin Ye

Dual-PWM Three-Level Voltage Source Converter Based on SVPWM

In order to overcome the shortcomings of traditional AC-DC-AC electrical driving systems, a dual-PWM method for the three-level voltage source converter to drive an induction motor (IM) is proposed in this chapter. In the rectifier part, this chapter presents the inner current-loop and the outer voltage-loop control strategy based on voltage space vector (SVPWM); in the inverter part, this chapter proposes the current-loop and the speed-loop control strategy based on SVPWM and rotor flux oriented. By applying the dual-PWM method, the system can get unity input power factor, minimize both input and output current harmonics, achieve bidirectional flow of energy, and enhance dynamic performance of the speed control. At last, both simulation and experimental results verify the feasibility and usefulness of this control method.

Chunyuan Bian, Xiaojun Duan, Xuehai Chen, Chonghui Song

Rectifier, Inverter, and Converter Technology (1)

Frontmatter

Control Strategy of Grid-Connected Inverter Suppressing Grid-Voltage Background Harmonics Based on the Improved Passive Damping Method

The traditional LCL-filter third-order system grid-connected inverter may cause the resonance phenomenon without damping. Also, it will be affected by the distorted grid-voltage background harmonics. In order to overcome the problem, a new control strategy is proposed. The chapter analyzes the current waveform performance of grid-connected inverter in the condition of grid-voltage background harmonics, which derive the feed-forward function for grid-connected inverter. The disadvantages of passive damping could be well solved by damping resistor virtualization of the original system, which realizes the active damping suppression of resonance. Simulation results based on the Heric single-phase transformerless grid-connected inverter verify the correctness of the

theoretical analysis

.

Zhiling Liao, Dong Xu, Shengdong Wang, Congli Mei, Guohai Liu

Control Methods for Tripled Structure NPC Inverter

Voltage waveform of single inverter contains more harmonics. In order to reduce the harmonic content, the H-bridge inverter with multiple structures was used to obtain a low harmonic voltage. However, this paper explored the multiple method based on the neutral point clamped inverter for obtaining the multiple circuit with lower harmonic content than the H-bridge multiple structure circuit. Further, it analyzed the advantages of output voltage waveform and harmonic suppression shown in an improved multiple structure inverter. Simulation waveforms confirmed the reliability of the theoretical analysis, proving that this method can obtain the ideal voltage waveform and reduce harmonics.

Cheng Zeng, Hong Zheng

Grid-Connected Inverter Control Technology Based on the Deadbeat Algorithm

Deadbeat control algorithm has good real-time performance and high precision, but it depends heavily on exact circuit system model. This chapter systematically studies the grid-connected current controlled by deadbeat algorithm in single-phase grid-connected inverter in different filter modes such as the single inductance

L

filter, the second-order LC (inductance and capacitance) filter and the third-order LCL filter. Based on the classical control theory, mathematical models of the inverter system were deduced in deadbeat control under the different filter conditions. And the design idea was described in the chapter. For the problem that resonance easily occurred in LCL filter, which brought difficulty in system design, two resonant rings in the circuit topology were inhibited by improving the structure of capacitance C. The computer simulation results showed that the waveform smoothness of grid current gradually improved with the increase in the number of filter order. At last, in a 3 kw prototype, the related hardware and software design were carried out, and the effectiveness and feasibility of high-order deadbeat control algorithm were verified.

Gujing Han, Wuzhi Min, Yunhong Xia

Improvements of Droop Control Strategy for Grid-Connected Inverters of Micro-Sources

Big droop coefficients tend to reduce stability of microgrid, while small droop coefficients result in slow responding of inverter. In order to overcome the disadvantage, we propose a kind of droop control strategy based on nonlinear droop characteristic which is similar to that of magnetic hysteresis. Through real-time changing droop gains appropriately, the proposed strategy is to improve load power distribution accuracy, effectively suppress the wide fluctuations of frequency and voltage, and improve the stability of the system. At the same time, adding a feed forward path on the power droop block further improves the stability. Then the reduced small-signal mathematical model of microgrid is developed, confirming the small disturbance stability. The time domain simulation is conducted in the power systems computer aided design. The results verify the effectiveness of the control strategy.

Yun Ling Sun, Guan Nan Wang, Wen Jun Wang, Dong Wang, Li Zhang, Wei Huang

Improved Ant Colony Optimization Algorithm in Inverter Fault Diagnosis

In this chapter, improved Ant Colony Optimization Neural Network (ACONN) is used to achieve inverter fault diagnosis. As the neural network is detachable, this characteristic is used to improve the neural network training efficiency of single ACONN. Matlab/m-file program is written to implement the improved algorithm. Improved ACONN is applied as the method of neutral network training to identify the 22 modes of inverter power semiconductor’s open-circuit fault. The results show that improved ACONN can reduce the computation amount and identify the fault correctly in comparison with that of single ACONN. Thus improved ACONN can achieve inverter fault diagnosis quickly and correctly.

Qinyue Zhu, Ying Wang, Xitang Tan, Yahui Zhao

Design of Flyback Converter Based on Synergetic Control

The general flyback converter is difficult to meet the overall stability of the converter when its input voltage and load have varied widely. The control strategy of the flyback converter based on synergetic control is proposed in this chapter, and it can be robust to both external disturbance and parametric variation. The results show that the synergetic control has constant switching frequency and better suitable for digital implementation; the manifolds can be reached from any original states according to exponential term; and the invariance against external perturbation and system parameter variation can be obtained when the matching conditions are satisfied. The simulation results of Matlab/Simulink show that the converter is not only asymptotically stabilized at the objective working point, but also has better robustness against the sudden change of input voltage and load.

Zhong Jianwei, Lang Jianxun

Model-Based Design and Verification of the Fuzzy PID Controller for a Digital Power Converter

Compared to traditional digital power converter system design, model-based design can significantly improve the development efficiency by using graphical modeling and simulation. This chapter describes a workflow that applies model-based design to develop a digital power control system for a half-bridge converter based on DSP TMS320F2812. In this workflow, the control loop of the converter is closely analyzed and reconstructed at the beginning. A DC/DC simulation model and fixed-point fuzzy PID controller model are then established. Combined with Matlab/Embedded Coder, peripheral drivers, as well as the asynchronous scheduler, are integrated, and the production-quality C code of the controller is also generated. Finally, the code is compiled and verified through software-in-the-loop (SIL) and processor-in-the-loop (PIL) testing. The result shows the efficiency of developing a digital power converter with model-based design.

Ming Zhu, Gaoming Liang, Kangwen Sun

Analysis of Power Loss in Transformerless Grid Connected PV Inverter

Efficiency is becoming increasingly important in grid connected photovoltaic inverter design. Transformer in grid connected inverter system is removed to improve the efficiency of the system. Traditional power loss calculation methods often neglected ripple current effects. However, photovoltaic inverters seldom operate at the maximum rated power due to variation of irradiation. Therefore, the ripple current effects on component power loss on the light load condition should not be neglected. The chapter analyzes the working principle of a transformerless grid connected inverter in detail, and establishes a mathematical model of component power loss which includes ripple current effects. An experimental prototype is made and experiment results verify the correctness of the theoretical analysis.

Zhiling Liao, Zhongqi Song, Dong Xu, Congli Mei, Guohai Liu

Rectifier, Inverter, and Converter Technology (2)

Frontmatter

Research and Design of Ignition System of Pulse Detonation Engine

In order to study the influence of ignition parameters on the operation performance of pulse detonation engine, an adjustment both in ignition energy and frequency ignition system was researched. Based on the study of topologies of power electronics, the buck DC/DC converter was adopted in adjusting input voltage, and an LCC series–parallel resonant inverter with step-up transformer was applied in boosting voltage while power transistors were employed in controlling the spark frequency to design the semiconductor low voltage-high energy ignition system. The control circuits of the main circuit and frequency controlling unit were also particularly designed. The analytical model of the converter is based on the basic circuit theories and the normalized averaging technique. The simulations of the circuit by MATLAB/Simulink show that both ignition energy and ignition frequency are controllable as expected, so the new designed system can meet the PDE’s requirements of the initiation system.

Jiyang Diao, Xiaosong Wu, Feng Feng, Hu Ma

Design of Self-Tuning Fuzzy PID Controller on PWM DC–DC Converter

In order to improve the performance of the PWM DC–DC converter whose controlling design is accompanied with complexities due to the inherently nonlinear characteristics, a novel controller is proposed in this chapter. By combining fuzzy control with conventional PID controller, the self-tuning fuzzy PID controller can adjust its own parameters to realize better performance for control systems. The simulation results showed an improvement in voltage control response in both steady and transient state periods in comparison with conventional PID method, and robustness was also validated. The proposed controller which incorporates the advantages of both fuzzy control and PID control can effectively improve the performance of the PWM DC–DC converter.

Zilong Yang, Yunyue Ye, Qinfen Lu

A Planar SJ IGBT with Plugged p+ Collector

In order to improve the performance of the superjunction (SJ) Insulated Gate Bipolar Transistor (IGBT), the plugged p

+

collector is implemented. By replacing the p

+

collector with an optimized combination of p

and p

+

collectors, it offers better blocking voltage and switching speed simultaneously. Simulation results show that the blocking voltage increases from 204 to 329 V by 61.27 % and the switching-off time reduces from 0.335 to 0.170 μs by 49.3 %. The proposed structure shows lower loss, higher breakdown voltage, and higher switching speed compared with conventional SJ IGBT. The optimized switching-off loss (

E

off

) and

V

cesat

trade-off makes the proposed structure suitable for high-speed and high-power applications.

Jiazhen Wu, Frank Jiang, Zhigui Li, Xinnan Lin, Jin He

An Improved Sliding Mode Variable Structure Control Algorithm and Its Application on PWM Rectifier

The ordinary PWM rectifier using the SMVSC (sliding mode variable structure control) is unstable before reaching the sliding surface and has non-removable buffeting, which leads to the contradiction between stability and rapidity. The VSC (variable structure control) is analyzed based on reaching law and a new method is proposed to achieve a better result in this chapter by combining the VSC with fuzzy control to regulate the reaching law of outer voltage loop. This method is compared with SMVSC without using fuzzy control and classical PI control by simulation under MATLAB/SIMULINK. The results show that this new method has the advantages in response time, overshoot, and system buffeting. The simulation results prove that this method can solve the contradiction between stability and rapidity, and it can be used in situations demanding high quality of direct current.

Hui-xian Huang, Xiang-ning Tang, Zi-bin Chen

Design of H Bridge Cascaded Filter and Bidirectional Converter for Railway Traction System

To develop a practical and efficient electronic device for compensating the negative, reactive and harmonic current in the railway traction system, the paper analyses the structure of the present railway traction system in China and its problems. Two topologies are proposed and analyzed to meet the special requirements in high voltage and power balance of the railway traction system. The H bridge cascaded two-phase active power filter can compensate the harmonic current and high voltage reactive power without separate DC source and transformer. The H bridge bidirectional converter can be parallelly connected to balance the power flow of the traction grid via two isolation one-phase transformers. The control circuit and system operation modes are also expatiated. Simulation results are given to verify the feasibility and effectiveness of the design.

Tian Mingxing, Zhao Qingchun, Yang Jianfeng

Modeling and Designing of Buck Converters Based on Voltage Mode Control

Based on the time-variant and the nonlinear characteristics of DC-DC Buck Converter, the chapter analyzes the converter’s operation mode and its working principle. The small signal mathematical model of Buck DC-DC converter operated in the continuous conduction is established by the use of the state-space averaging method, and the closed-loop control system of voltage mode control with the model is built as well. The waveforms of simulations of typical Buck converter circuit model and state-space averaging mathematic model are compared with the MATLAB software and simulation results fitting the theoretical analysis shows the validity of the proposed modeling method. The simulation result of the closed control system of voltage mode control shows that the system is stable. The method to determine the parameters of DC-DC converter is also presented in the chapter.

Qi Xu

Fuzzy-Based Direct Power Control on Elevator System with Energy Feedback

In order to save the regenerated power energy and improve the power quality of the traditional variable voltage variable frequency (VVVF) elevator, a new energy feedback elevator system is presented in this chapter. The shunt converter is used here to offer a feedback path for the regenerative energy and to eliminate the harmonics. This chapter proposes a novel direct power control (DPC) based on fuzzy-logic to control the shunt-converter that is appending to the elevator. In terms of the instantaneous power theory, the novel DPC scheme regulates the instantaneous active and reactive power simultaneously by tracking the power errors. Without hysteresis comparators, the proper switching states of the converter are selected according to the fuzzy logic rules, in accordance with the input fuzzy variables and the voltage sector numbers. The simulation results verify that the regenerated energy could be fed back to the mains, and at the same time, sinusoidal grid current and unit power factor could be achieved. The new energy feedback elevator system has excellent steady and dynamic performance while the power quality is enhanced.

Xiaofeng Zhang, Xiaohong Wang, Quanxue Guan, Lianfang Tian, Haixia Zhang

Electrical Machines and Drivers (1)

Frontmatter

A New Online Identification Method for X q of Synchronous Generator with Steady-State PMU Data

The accuracy of synchronous generator’s reactance parameters is fundamental for power system stability analysis. This chapter proposes a new online identification method for synchronous generator’s quadrature-axis synchronous reactance

X

q

with PMU (phasor measurement unit) steady-state data. In detail, based on the steady-state PMU data including the terminal voltage, terminal current, active power, reactive power, and power angle, the proposed method formulates the identification of

X

q

as an optimization problem which aims to minimize the difference between the calculated terminal voltage and measured terminal voltage, and the objective is set as the sum of the square of the difference. The proposed optimization is solved by least square method. Simulation results with PSCAD verified the high accuracy of the proposed method. Furthermore, simulation results with field steady-state PMU data show the effectiveness of the proposed approach.

Junli Zhang, Ancheng Xue, Tianshu Bi, Zhengfeng Wang, Wei Tang

Controlling of Double Y Shift 30˚ PMSM Series-Connected System Based on SVPWM

A number of multiphase motors can be series-connected and driven by a single inverter via the appropriate phase transformation rules, and all motors in series can be independently controlled. In this chapter, the working principle of two double Y shifts 30° permanent magnet synchronous motor (PMSM) series-connected system is proposed, a novel SVPWM method to achieve decoupled control of the series-connected system is presented. The implementing method of SVPWM is given. In Matlab/Simulink, the motor operating conditions under variable load and variable speed via id = 0 vector control strategy are analyzed, and the feasibility of the proposed SVPWM control strategy is verified.

Shi Xianjun, Liu Lingshun, Zhou Shaolei

Calculation of Rated Load Voltage for Permanent Magnet Motor by Finite Element Method

In order to calculate the rated load voltage of direct-driven permanent magnet synchronous generator, two different finite element methods are used. First, a mathematical model of electromagnetic field and a field-circuit coupled model of transient electromagnetic field are established. And then transient electromagnetic field, which can better reflect the transient process of the permanent magnet generator at rated load, is simulated to obtain the stator winding voltage by Ansoft software. Finally, the simulation results are verified to be correct by load current iteration method. Lots of references have proved that the finite element method can effectively calculate the load voltage which can be applied to engineering practice and should be popularized.

Bing Guo, XinZhen Wu

Control of Permanent Magnet Synchronous Motor Based on Sliding Mode Observer

In order to achieve the sensor-less vector control of permanent magnet synchronous motor and estimate the position and speed of motor rotor, a new technology of detecting sensor is proposed by using the sliding mode variable structure theory. By introducing a saturation function in replace of the traditional switching function, the technology solves the problem of chattering in high frequency. A model is established in the environment of MATLAB/SIMULINK to simulate the system through theoretical analysis. The simulation shows that we can estimate position and speed of PMSM precisely through the sliding mode observer, and we can also gain a better result in the experiment by using the new technology. Finally, we can conclude that we can improve the robustness of the system by changing certain parameters and the estimation of the position and speed by using the sliding mode is effective (Canadian Conference on Electrical and Computer Engineering, vol. 2:689–692, 1994).

Jiebing Mao

No-Coupling Test Method for Brushless DC Motor Based on Model Identification

In order to reduce the complexity of traditional motor test, this chapter presents a no-coupling test method for brushless DC motor based on parameter identification techniques. Based on the motor’s dynamic mathematical model, the parameters, such as the motor coil resistance, back EMF coefficient, rotary inertia, and damping coefficient can be obtained just through measuring the motor input voltage, motor current, and motor speed. The motor’s characteristics and other physical parameters can also be obtained based on the identified parameters. Simulation result validates that the test method is feasible and has high precision. The no-coupling test method provides an easy and quick method and can effectively solve the problem of traditional motor test.

Deshun Yan, Xu Liang, Jian Huang, Hong Guo

Sliding-Mode Variable Structure Controller for Stator Flux and Torque of Induction Motor Drives

Good flux and torque control performance is vital to high performance AC servo drives. A sliding-mode variable structure controller (SM-VSC) for stator flux and torque of induction motors is presented in this chapter. From the mechanism model and electromagnetic characteristics of IM, it is proved that the coefficient matrix

D

is non-singular and that the SM-VSC for stator flux and torque of IM is feasible. In order to reduce its inherent chattering and resulting ripples of torque and flux, an exponential reaching law is chosen, in which the parameters are designed by Lyapunov’s theory under satisfying some robustness in the presence of parameter and disturbance uncertainties. Simulation results are presented to show the capability and validity of the proposed control scheme.

Qinghui Wu, Lin Li, Shuxian Lun

Study Tip Leakage Vortex of CPU Fan with Skewed Rotors

In this chapter, to obtain the characteristics of tip leakage vortex in the flow field of CPU fan with skewed rotor, the tip leakage flow fields are used to investigate the three fans with three kinds of circumferential skewed rotors, including the radial rotor, the forward-skewed rotor, and the backward-skewed rotor. By computation, based on the method of the eigenmode analysis of the origination position of tip leakage vortex, the development of vortex strength can be displayed clearly. In the experiments, the two-dimensional plane particle image velocimetry (PIV) system is used to measure the flow fields in the tip region of three different pitchwise positions of each fan. The results show that in comparison with the radial rotor, the other two skewed rotors can increase the stability of the tip leakage vortex and the increment in the forward-skewed rotor is more than it is in the backward-skewed one. Among the tip leakage vortices of the three rotors, the velocity of the vortex in the forward-skewed rotor is the highest in the circumferential direction and the lowest in the axial direction.

Li Yang

Electrical Machines and Drivers (2)

Frontmatter

Test Platform of Fuel Cell Electric Vehicle Powertrain

A simulated test platform of fuel cell electric vehicle (FCEV) Powertrain was built, which includes fuel cell system, battery pack system, unidirectional DC/DC converter, test motor system, AC dynamometer, etc. The Powertrain test of FCEV can be accomplished on the platform. The energy management system (EMS) was designed to control the Powertrain power flow. The use of standard driving cycles allowed for verifying the control effect of EMS. Taking for example the Economic Commission for Europe driving cycle, which presents the start-up mode, accelerating mode, and braking mode of the vehicle, the simulation results were obtained and analyzed. Results indicated that the EMS was efficient and the Powertrain had good dynamic performance and high driving efficiency. This platform proved to be a useful tool for the research and development of FCEV.

Changjun Xie, Qin Zhang, Shuhai Quan

Analytical Model of Adjustable Permanent Magnetic Coupler with Monolayer Conductor Rotor

In order to optimize parameters of adjustable permanent magnetic coupler quickly, this chapter designs a simple analytical model to find out the internal relations of design parameters. Based on linear theory, the 3D problem is transformed to a 2D one and the analytical model is established by the variable separation method. 2D finite element method is used for modeling analysis of adjustable permanent magnetic coupler to prove effectiveness of analytical model. Simulation results show that the presented analytical model can effectively reflect the effect of parameters on equipment performance which proves that it is a rapid analysis tool. In addition, structure with multilayer conductor rotor is considered. The comparison results of two different structures show that multilayer structure is obviously superior in improving transmission torque.

Xu Wang, Dazhi Wang

The Modeling and Excitation Characteristics of the Transformer Under DC Bias

In order to research the influence of DC bias on the transformer, a transformer modeling method under DC bias is proposed. Based on the JA (Jiles-Atherton) theory, the method establishes the dynamic core magnetization curves of considering hysteresis. Then the transient transformer model is built through deriving the transformer equation from unified magnetic equivalent circuit model. On the different DC bias, the model is used to simulate the core magnetization characteristics, excitation currents, and harmonic changes of the no-load transformer. The results show that the model can be an effective means to research the excitation characteristic when transformer is under DC bias.

Dongwei Han, Tao Zheng, Xianqi Zhu, Huanhuan Qi

Energy-Saving Research on Asynchronous Motor Voltage Regulation Using Γ Equivalent Circuit

In order to study the energy-saving control of the motor terminal voltage regulating according to the load change, this chapter investigated the asynchronous motor loss based on the Γ-shaped equivalent circuit. The electrical loss in the motor is divided into two parts, of which one is the loss with the terminal voltage changes and the other is the loss with the load changes. And the calculation formulas about the two kinds of loss are derived. The mathematical model is obtained which reveals the relation of the minimum loss corresponding to the optimal operating voltage. Considering the practical application, the calculation method, which computes the optimal motor operating voltage, is obtained. In the computing model, the input power and the stator voltage are treated as the measurable inputs. The experimental results show that the voltage regulation method can improve the operating efficiency of the asynchronous motor, especially in the conditions of light load at which the energy-saving effect is more pronounced. In the case of variable load, the calculating method getting the motor’s optimal operating voltage based on the field online measurable inputs can satisfy the requirement of voltage regulating and energy saving in the asynchronous motor. The method also has the characteristics of good engineering applications and real-time property and can achieve a good energy-saving effect.

Ronghua Li, Si Li

Transient Performances Analysis and Experiment for Optical Current Transformer

For qualitatively investigating the influence of the optical current transformer (OCT) on the protective relays, transient performances of OCT were theoretically analyzed based on the signal processing method of amplitude detection of single optical path, and it was also proved simultaneously that the aperiodic component influences the OCT output. Relay test equipment generated the high short-circuited current, and simulated transients were caused by a short-circuit fault. Field fault recording data-based COMTRADE standard format was obtained and event representation software of relay test device was also employed to simulate single-phase-to-ground fault and phase-to-phase fault, respectively. Transient response waveforms in the laboratory measurements of standard reference current transformer (CT) and OCT were recorded and compared with the fault recorder in the field individually. Laboratory research and experience show that OCT can reproduce the transient signal of electric network more accurately than conventional CT. Measuring records were also obtained and evaluated to verify that the optical systems might be more suitable for replacing conventional CT. Furthermore, empirical results also confirm that OCT has better frequency response than conventional CT.

Hongbo Li, Xingguo Cai, Guoqing Zhang, Zhizhong Guo

Double-Motor Synchronous Control System Based on Deviation Coupling Strategy

The chapter describes a math model of double-motor synchronous control system based on deviation coupling strategy by MATLAB/Simulink. Two identical brushless DC motors were studied as research objectives for the synchronous control system. Aiming at synchronous performance of double-motor being at a low-level with load disturbance, deviation coupling strategy based on intelligent PI was employed to control the double-motor keeping in sync. Comparing with traditional PI control system, the intelligent PI control system successfully solved the contradiction between quickness and smoothness. Simulation results were illustrated to show a good performance in the deviation coupling control system by adopting proposed scheme.

Li Zeng, Zicheng Li

Active Filters and Harmonics

Frontmatter

An Auto-Tuning Filtering Method Based on Variable Reactors

An auto-tuning filtering method based on the variable reactor is presented in this chapter. As the inductance of the traditional passive filter is constant and the capacitance is affected by temperature as well as the other external factors, the resonance frequency of the filter may deviate from the resonant point. To deal with this drawback, an auto-tuning filtering method based on the variable reactor is presented. The inductance of the variable reactor can be adjusted by adjusting the triggering angle of the thyristor, the equivalent inductance of the variable reactor would be changed automatically, and the filter would be retuned to the harmonic frequency. Simulating analysis shows that the accuracy and feasibility of this method are good. The harmonics of the power grids will be suppressed. And the power consumption of the equipment would be reduced as well.

Haiping Lin, Jing Chen, Siyu Huang, Youxin Yuan

The Reverse Reactive Power of SVC in the Field of the Electric Arc Furnace’s Reactive Power Compensation

Against the problem of reverse reactive power of SVC existing in the electric arc furnace’s reactive power compensation, this chapter uses adjustable power factor instead of fully compensation, that is, a mode in which the power factor is equal to one. Via the simulation analysis, this chapter verifies the effect on solving the reverse reactive power within the mode of adjustable power factor.

Jinfa Fu, Zhenyu Xu

Design of Phase-Locked Loop Circuit Based on Ant Colony Optimization Algorithm

In order to optimize the parameters of phase-locked loop circuit, an analysis of the stability and principle of phase-locked loop circuit is put forward by intelligent control theory, and its mathematical model and transfer function are established. And then, a parameter optimization method based on ant colony algorithm is proposed. The experimental results show that the phase-locked loop circuit designed in this method can supply a stable and accurate trigger signal. So this method can be applied into the phase-locked loop circuit for a great synchronous sampling required.

Dazhi Wang, Liang Qiao, Xifeng Guo, Zhen Liu

Combined Exact Feedback Linearization and Double Hysteresis Control for Active Power Filter

In order to improve the performance of active power filter (APF), a novel compound control method combining input/output exact feedback linearization and double hysteresis control for shunt APF is proposed in this chapter. By the application of input/output exact feedback linearization theory, the model of APF under the synchronous orthogonal “

dq

” frame is decoupled. A new method to calculate the reference voltage vector of the double hysteresis system through the control variables of main circuit’s switch function under the synchronous orthogonal “

dq

” frame is proposed. With the double hysteresis pulse width modulation (PWM) strategy based on voltage space vector, the switching frequency of APF is reduced efficiently and the dynamic performance of the whole APF system is improved. Simulation results showed that the system had good compensation performances in both steady state and transient operation based on the proposed compound control method. Besides, the system is characterized by a fast dynamic response and reduced switching frequency. After the compensation, the total harmonic distortion (THD) of the power source currents in steady state is limited to fewer than 2%.

Guohai Liu, Chenxing Yang, Zhaoling Chen

The Application of Fuzzy PI Compound Control to DC Bus Voltage Regulation

According to the large overshoot and high static error of traditional Direct Current (DC) bus voltage control, DC bus system model of active power filter (APF) was built on the basis of analyzing APF DC bus voltage control theory, and a new DC bus voltage control method based on combination of Proportion Integration (PI) control and fuzzy control was proposed; then an experimental prototype was built. Simulation and experimental results indicate that the method has features of fast response, small overshoot, and small static error. All the features above prove that the method is effective and feasible.

Xifeng Guo, Dazhi Wang, Zhen Liu, Fenglong Shen, Wei Han

Power Supplies and Power Sources, Electromagnetic Compatibility

Frontmatter

Design of Numerical Control Power Supply System for Gas-Sensing Test Instrument

In order to reduce the researchers’ workload in testing gas-sensing materials, a numerical control power supply system is proposed in this chapter. The power supply system is used to heat the gas-sensing materials. In this system, multistep input voltage is designed for the purpose of enhancing efficiency and negative feedback network is used to ensure the stability of the output voltage. An excellent linear relationship between the temperature and voltage of the ceramic heating plate has been found, which can be made use of in the software design. Test results show that this system has excellent properties such as fast dynamic response and high efficiency and provides a great convenience for gas-sensing materials testing.

Gaochen Gu, Shengquan You, Xun Liu, Jinming Wang, Guolong Liu, Hao Cai, Hui Suo

The Mid-Frequency Power Research Based on Multiple Closed-Loop Feedback

In order to solve the grid harmonic current pollution of nonlinear rectifier and the power factor change, the 400 Hz mid-frequency power supply was studied in this chapter. By adopting active power factor correction circuit in the input of inverter power, the harmonic current can be reduced and the input power factor can be improved when the voltage is in sag. The inverter output can cause distortion of the output voltage waveform and bad real-time RMS feedback when it is with nonlinear loads and in dead zone, etc. This chapter proposed a multiple closed-loop feedback control strategy to solve this problem, i.e., the capacitor current was inner loop, voltage was mid-loop, and RMS or the amplitude was outer loop. The chapter used the instantaneous reactive power theory and

abc

/

dq

0 transform on the current and voltage detection to improve the real-time RMS feedback. It was verified on the experimental platform controlled by DSP2812 and the results confirmed the viability and effectiveness of the proposed method. The mid-frequency power system with high power factor and multiple closed-loop feedback had both fine static characteristics and improved dynamic performance. It can improve the power factor and reduce the grid harmonic pollution.

Su-ping Pei, Xiao-lei Wang

A Study on the Model of Electric Vehicle Charger and Battery

In order to promote the research on the load modeling of the electric vehicle (EV) charging, this chapter established models of EV’s charger and battery. Firstly, it analyzed and chose the structure which is made up with uncontrolled rectifier and chopper as the main structure of the EV’s charger, and then it built the simulation model using Matlab/Simulink software. Secondly, some battery models were analyzed and the lithium-ion battery model which can be equivalent to a controlled voltage source in series with internal resistance was chosen, based on which the simulation model in Simulink was built. Thirdly, the model of charging station was simulated and the curves were analyzed which include voltage, current, and active and reactive power waveforms when EV’s charging. The result of simulation showed that the models met the design’s requirement. EV consumed active power mainly and remarkably and uncoordinated charging would result in increment of the distribution system loss. Finally, it was concluded that EV charging has the characteristic of impact load and EVs’ coordinated charging control should be done.

Zhiyong Liu, Zengping Wang

Fuzzy Sliding Mode Control of Air Supply Flow of a PEM Fuel Cell System

To reduce the danger of the oxygen starvation of the proton exchange membrane fuel cell (PEMFC) stack and improve the net power output of the PEMFC system, the air supply flow of the PEMFC stack must be regulated effectively. The nonlinear and time-variant characteristics of the PEMFC air supply system make it difficult to adjust its air supply flow for traditional control strategies. A fuzzy sliding mode controller (fuzzy SMC) with good robustness is proposed to control the air supply flow of the PEMFC stack in this chapter. An equivalent control is constructed based on the developed model of the PEMFC air supply system. A fuzzy logic inference mechanism is embedded in the traditional SMC to generate a smooth hitting control. Numerical simulations show that the proposed fuzzy SMC removes the chattering phenomena of the traditional SMC. Compared with the static feed-forward (sFF) controller, PI controller, and PI/sFF controller, the fuzzy SMC provides much better control performance of the PEMFC air supply flow.

Chun-hua Li, Zhen-hua Sun, Yu-long Wang, Xue-dong Wu

Modeling and Performance Analysis of a PEM Fuel Cell System

Models of a proton exchange membrane fuel cell (PEMFC) system are presented for the performance analysis and controller design. The electrochemical model, the cathode and anode pressure model, the thermal model, and the air supply model of the PEMFC system are developed. Based on the simulation results, the effects of operating pressure and temperature on the cell V–I performance, the inlet composition of the cathode and anode, and the cell efficiency are analyzed.

Chun-Hua Li, Xiao-Peng Ji, Qing-Jun Zeng, Yu-Long Wang, Xue-Dong Wu

The Modeling Method of Electromagnetic Interference of Double Observation Point Electric Equipments

An identification method of conducted electromagnetic disturbance from electrical equipment is proposed. Single supply dual power supply network is modeled by the method. The network model is nonhomogeneous differential equation of conducted electromagnetic disturbance. It is tested that the two switching power supplies of the carrier frequency are 30 and 40 kHz on power supply network. The experimental result shows that norm of nonhomogeneous term is 9.59 × 10

13

and 3.03 × 10

13

in the conducted electromagnetic disturbance differential equations, and the method is effective to achieve the identification of the switching power supply and independent of load fluctuations. The method has a good recognition effect and a small amount of calculation. Using the approach helps improve the flexibility and intelligence of the smart grid demand forecasting.

Dong Yan, Xiaoping Zeng, Zhang Kai

Electromagnetic Compatibility of Metallic Enclosure of EV Battery Management System Based on FEM

Electromagnetic shielding effectiveness of metallic enclosure influences the EMC performance of EV-BMS (electric vehicle-battery management system). Electromagnetic leakage of electric equipment enclosure caused by apertures is a serious problem. In this chapter, the numerical simulation analysis for electromagnetic shielding performance of enclosure with apertures is performed based on Finite Element Method. Different shapes and orientation of aperture/slot bringing to shielding effectiveness and resonant frequency are analyzed, and analysis of the influence on the shielding performance of the enclosure by the different location of aperture is conducted as well. Meanwhile, some improving counter measures are proposed. By comparing different schemes of BMS metallic enclosure, the chapter provides guidelines for designing the enclosure.

Chang-qun Wang, Xue-ming Sun, Chun Cai, Fan-shui Lu, Qiang Ye, Jian-hua Li, Li Wu

Energy Conversion and Management

Frontmatter

Application of Fuzzy Clustering Analysis in the Energy Systems Comparison

In recent years, the issues of sustainable development of energy-economy-environment are causing concern to researchers and government officials. The development planning of energy systems is a hot topic. In the comparative analysis of energy systems, the commonly used method is the trend comparison of indicator data. This chapter compares the basic indicator data of energy systems of 11 provinces and cities in 2002 where the fuzzy clustering analysis is used. In this chapter, the equivalent matrix is gotten through using the transitive closure method, combining Boolean matrix method and

F

-statistics to find the best classification results. Referencing that year’s energy intensity index value from a macro level, the development proposals of energy systems can be given.

Xinke Ma, Xiaoliu Shen, Zhiyao Li, Qiangzhi Li

Optimal Model for Overall HVAC System

According to the problem that the components of HVAC (Heating, Ventilating and Air Conditioning) system have strong coupling and low energy efficiency, an optimal model for HVAC based on system energy input ratio (SEIR) is proposed. Firstly, according to each equipment characteristic, the performance curve model of each equipment power was built. Basing on these models, the performance curve model of system energy consumption was built too. Then, basing on three kinds of constraints, that is, energy conservation constraint, performance constraint, and coupling constraint, the constraint equation was built as well. Finally, by simplifying the model parameter and taking the least energy input ratio as an objective function, the optimal set point model of various equipments was established. The experimental results indicated that compared with the least energy consumption optimal method, the system power at minimal SEIR was improved by 6.89 %. It proved that the model can obtain better energy saving effect.

Ma Qing, Wu Hao

Wind Energy Systems

Frontmatter

Wind-Thermal Power Random Multi-objective Scheduling Based on PLSPP-MIPSO

The grid-connection of large scale wind power to dispatch system will bring new uncertainty since wind power has great randomness and uncontrollability. To solve this issue, this chapter constructs the wind-fire random optimal model by using the partial least squares projection pursuit coupling (PLSPP)-multi-objective immune particle swarm (MIPSO) algorithm. The advantages of the combined arithmetic are highly distributed of solution and convergence. Consequently, the multi-objective optimizations on the minimization of power cost and pollution emissions of thermal power units can be achieved. Finally, an example of IEEE-30 node is given to demonstrate that the optimal solution of the multi-objective optimizations can be derived. It indicates that the solution with the highest degree of coordination and the output plan of specific unit at each stage are obtained. The research shows that the proposed method has significant results in theory and industrial applications.

Lu Min, Zhao Mi

Reactive Power Compensation Strategy of DGIF Wind Park

In this chapter, two different wind park reactive power compensation strategies for the DFIG wind park connected to the sub-transmission level are proposed. Except considering DFIG wind turbines as dynamic reactive power compensator, some extra reactive compensation equipments such as capacitor banks and STATCOM are installed at the wind park substation level. The dispatch method of reactive power compensation size among capacitor banks, and DFIG wind turbines and STATCOM is studied. Finally, with DIgSILENT software, the performances of different reactive power compensation strategies in steady state are tested by simulation.

JingJing Zhao, Yang Fu, DongDong Li, KaiKai Wang

The Largest Wind Energy Capture Based on Feedback Linearization Control

In order to achieve maximum wind energy capture in the wind power system operation, this chapter presents a feedback linearization control strategy. This chapter establishes permanent magnet synchronous wind power system simulation model in the Matlab/Simulink environment, by using the simulation software to simulate the tip speed ratio, rotor speed, and wind energy utilization factor, it proves the effectiveness of this control strategy. The simulation results show that the simulation curves of the tip speed ratio and wind energy utilization factor reach stable level at their respective best value, and the fluctuation range is very small. The trajectory of actual rotor speed is always to follow the trajectory of the optimal rotor speed to change, and it can track the optimum rotor speed very well. The feedback linearization control strategy is feasible and effective, and achieves maximum wind energy capture.

Huang Yuehua, Li Huanhuan, Li Guangxu, Yuan Chunguo

A Novel Hybrid Approach for Wind Power Forecasting

This chapter proposes a hybrid approach for wind power forecasting based on autoregressive integrated moving average and back propagation neural network, which employs a new combination mode. The model took into account the wind speed, wind direction, and the physical limitations of the wind plant. Compared with the real data of a wind plant, the analyzing result shows that the proposed method improves the accuracy of wind power prediction effectively, and it also has good practical value.

Xiang Xue, Dong-mei Zhao, Huan-huan Dong, Jin-yi Wang, Wen-hui Zhao

Prediction of Short-Term Power Output of Wind Farms Based on Extreme Learning Machine

Due to the fluctuation and intermittency of wind power, wind power forecasting is an effective way to reduce its impact on power system. This chapter introduces extreme learning machine (ELM) for wind power generation prediction of a wind farm. ELM has the advantages of small training error, small weight norm, fast training speed, and high generalization performance. The weather forecast data and power output of wind farm were set as samples to build the neural network model of predicting wind power based on ELM. In order to verify the advantages of the ELM model, the estimation results of ELM and BP neural network were compared. Finally, it was found that the prediction accuracy and generalization ability of ELM in wind power prediction was satisfactory, and it had the superiority of simple implement and fast estimate.

Zhang Zheng-zhong, Jia Yi-min, Zhao Wen-hui, Xia Tian

Short-Term Wind Power Forecasting Based on Lifting Wavelet, SVM and Error Forecasting

In order to improve the forecasting accuracy, a novel forecasting method using wavelet, support vector machine (SVM), and error forecasting technology is presented in this chapter. Firstly, it utilizes lifting wavelet method to decompose data to extract the data’s main characteristics. And then it establishes the SVM forecasting model and error forecasting model to realize the wind power load forecasting, relative error forecasting, and wind load data correcting. Finally, the actual data is adopted for simulation. The experimental results show that the method based on lifting wavelet transform, SVM, and error forecasting can improve the forecasting accuracy greatly. The test shows that the method used for the wind power load forecast is feasible and effective.

Jinbin Wen, Xin Wang, Lixue Li, Yihui Zheng, Lidan Zhou, Fengpeng Shao

Reactive Power Optimization for Wind Power System Based on Adaptive Weights Flight Adjustment Particle Swarm Optimization

In recent years, the uncertain output of wind power has had growing effects on the regional power grid. Reasonable reactive power optimization can effectively improve the adverse effects of wind power. In this chapter, an Adaptive Weights Flight Adjustment Particle Swarm Optimization (AWFAPSO) is proposed for the reactive power optimization of wind power system. First, it established a mathematic model in which system active power loss will be treated as objective function, and adopted penalty function to process node voltage cross-border and generator reactive power cross-border. Then AWFAPSO was presented. Using variable inertia factor, it can locally regulate the flight speed of the particle which leads to finding the optimal solution effectively and adopting adaptive flight time to guarantee the flight convergence in general, thus preventing particles from oscillating near optimal solution in the late of conventional particle swarm. Finally, the simulation shows that reactive power optimized by AWFAPSO can effectively reduce the system loss and improve the node voltage level.

Xi Wang, Xin Wang, Lixue Li, Yihui Zheng, Lidan Zhou, Yang Liu

Equivalent Models of Wind Farms with Fixed Speed Wind Turbines

In order to simplify the model of wind farms in power system simulations, an equivalent single wind turbine model is presented as the model of wind farms in this chapter. By using a new way to obtain equivalent wind speed, the equivalent model can represent wind farms very well. For illustration, a detailed model and an equivalent model are built and their steady and dynamic performances are compared to show the feasibility of the new way in PSCAD/EMTDC. The simulation results show that errors between the two models are minute under wind speed fluctuation and grid disturbance. The new way to calculate equivalent wind speed is effective and the equivalent model can be used to replace the detailed model of wind farms in power system simulations.

Jianming He, Lin Guan, Xinming Fan

Solar Photovoltaic Devices and Systems

Frontmatter

Hybrid Power System Composed of Photovoltaic and Commercial Power

As an important application of solar energy, photovoltaic generation has attracted more and more attention. But there are some disadvantages in the perspective of solar energy, such as dispersion, intermittent, and randomness, which cannot provide stable and consistent power and should be equipped with additional energy. This chapter chooses commercial power as the back-up energy and proposes a hybrid power system with both photovoltaic and commercial power. The system is composed of a solar cell, the commercial power, a DC–DC(direct current) converter, a power factor correction (PFC) converter and DC load. In order to utilize the solar energy as much as possible, a power management is necessary for the hybrid power system. The core of the energy management strategy is to keep the system work under suitable mode to control the energy flow of the system according to the work status of the solar cells and the load. The experimental results verified the effectiveness of the energy management strategy.

Liao Zhiling, Wu Ben, Xu Dong, Mei Congli, Liu Guohai

Optimal Power Smoothing Control Strategy of Photovoltaic-Energy Storage System Based on a Fast Particle Swarm Optimization

Photovoltaic power generation has become one of the state’s strategic emerging industries. So the related technology is more and more important. Since the power of photovoltaic system fluctuates randomly, it has drawn much attention to smooth the power output of photovoltaic power generation. An optimal power smoothing control strategy of photovoltaic-energy storage system (PESS) is proposed based on fast particle swarm optimization (FPSO). First, it presented a new mathematical model which contains three PESS cost index including power generation, environmental pollution, and waste of resource. Then, it implemented a new renew strategy. In the former part of renew strategy, the traditional method is used to enhance the global searching ability. While in the latter part, the steepest descent method is applied to improve the local searching ability. The validate results verified that the method is accurate, fast, and easy to be put into practice of realizing optimal power distribution.

Jing Ma, Jianlei Shi, Zengping Wang

A Novel Global Maximum Power Point Tracking Scheme Under Partially Shaded Conditions

Under partially shaded conditions (PSCs), multiple peaks appear on the power-voltage curve of the photovoltaic (PV) array, which makes it difficult to track the global maximum power point. To address this issue, we first analyze the nonlinear characteristic of PV array under PSCs. On this basis, a novel global maximum power point tracking scheme is proposed, which consists of two major subroutines: genetic algorithm (GA) and 5-dot perturbation and observation (P&O) method. The GA subroutine is used to shift the operation point to the vicinity of the global peak, and 5-dot P&O subroutine is used for accurate tracking. The validity of the proposed scheme is verified by experimental results.

Xiaodong Lu, Renjian Feng, Shuai Zhao

Photovoltaic Planning Process for Untypical Region

The power generated by PV arrays or cells could be reduced by the case of shadow loss. This chapter mainly focuses on how to gain the maximum power for a solar farm after considering the influences of spacing, tit angle, and azimuth angle on the planning fields. A mathematical model is proposed firstly, during the process of planning the PV array located in Nanjing (32°N, 118°E), the influences on the productivity of it caused by the different types of photovoltaic cells and different arrangement programs are discussed then. Corresponding results show that the station can get the maximum generation power by choosing KD210GH-2PU cells with scheme 1. The results above also indicate that the mathematical model and the process presented are suitable for the practical engineering application.

Haixiang Zang, Qingshan Xu, Lulu Ji, Wei Wang, Haihong Bian

Analog Circuits and Data Conversion Circuits

Frontmatter

A New Color Interpolation Algorithm for Bayer Pattern Digital Cameras Based on Green Components

To judge the smooth area or edge in an image accurately and reduce false color caused by different channels with different orientation judgment, a new color interpolation algorithm based on the difference of Green channel’s orientation-gradient is introduced. By introducing horizontal gradient and vertical gradient, the smooth area or edge and the interpolation orientation of the Green channel can be judged by the two gradients. Once the interpolation orientation of the Green channel is fixed, the restoration of Red or Blue channel will be decided by it to reduce false color. Experiments show that the algorithm achieved a high peak signal-to-noise ratio (PSNR) and good image quality not only on the edge but also in the smooth area and the false color is reduced too. Combining the advantages of the edge-sensing and bilinear interpolation, the new interpolation algorithm can achieve a better quality on the whole image.

Huaping Ma, Shuang Liu, Guanglu Wei, Zunlie Tang, Shangjian Zhang, Yong Liu

Analysis of Image Intensifiers Halo Effect with Curve Fitting and Separation Method

In order to probe into the halo effect for image intensifiers, we have deduced the fitted formula for the gray value distribution (GVD) of pixels on a centerline through the center point of halo images by the numerical theory of Gaussian curve fitting and analyzed the halo effect with the curve separation method. By the image translation processing, the approximate point spread functions (PSFs) for the halo test device and image intensifiers are obtained respectively. The results show that the GVDs of pixels on the centerline in halo images for the test device and low light level (LLL) image intensifiers all consist of two curves. One curve is the Gaussian distribution curve (GDC) and the other is a straight line with the same gray value. The straight line is regarded as the background noise. After the super second generation (Gen II+), the image intensifier is put in the halo test device. Half the width of GDC for the collected halo image is smaller than that for the third generation (Gen III) one. This research is helpful for exploring the formation mechanism of halo effect and beneficial to promote the development of the LLL night vision technology.

Ling Ren, Feng Shi, Hui Guo, DongXu Cui, Yunsheng Qian, Honggang Wang, Benkang Chang

Sparse Reconstruction Using the Integrated Approach for Magnetic Resonance Imaging

In order to decrease the number of data sampling and scan time in magnetic resonance imaging, a sparse reconstruction approach is proposed in this chapter. Integrating the conjugate gradient and orthogonal projection with line search, the proposed approach can solve both the convex problem and the nonconvex problem in the image reconstruction. Two imaging examples are illustrated in this chapter. Experimental results show that the better quality can be obtained when the proposed approach is used for nonconvex reconstruction than convex reconstruction. The proposed approach can effectively solve the optimization problem for sparse imaging; thus the magnetic resonance images can be reconstructed under highly under-sampled rate.

Yu Lu, Hua-Hua Chen

Automated Estimation of Ore Size Distributions Based on Machine Vision

Ore image segmentation is the most important and difficult step for automatic estimation of the ore size distribution. In this chapter, we propose a method for the segmentation of ore images in an ore size distributions system based on the machine vision. Firstly, the method uses mean shift algorithm to detect the dark areas among ore particles. And then a series of filtering, threshold, morphologic operations, and watershed transform processes are designed to determine ore particle sizes from digital images. The experimental results show that our method can separate ore particles accurately and automatically estimate the size distributions.

Ke Dong, Dalin Jiang

Automatic Building Detection and 2D Footprints Reconstruction for VHR SAR Images

A novel method for building detection and 2D footprint reconstruction for very high resolution synthetic aperture radar was proposed. In the detection part, the generalized gamma distribution (G-Gamma) was firstly used in CFAR (constant false alarm ratio) detection for better modeling both of the homogeneous region and heterogeneous region in SAR image. Because our interests in this chapter focus on the rectangular buildings, some criteria were used to select buildings from all the detection results. In the reconstruction part, optimal rectangular was used to fit the boundaries of the building candidates. Compared with the reference data, experimental results indicate that the proposed method is proved to be with high correct detection ratio and positioning accuracy. For further study, the ground truth data of an interesting area was also measured, and the result shows that the estimated size has a good relationship with the real size of the building.

Yanan Zhu, Zhen Li

A Novel Video Super-Resolution Algorithm Based on Non-Local Normalized Convolution

At present, most of video super-resolution reconstruction algorithm make the reconstruction result blurred, especially around the edges. In order to solve this problem, we study the basic theory of normalized convolution (NC), which include the NC based on polynomial basis function and the least-square solution and propose a novel video sequence super-resolution reconstruction algorithm based on non-local normalized convolution in this chapter. This algorithm can be combined with gray-value information and structural details in the image. The density of sampled data and local structure in edge decide the shape and size of neighborhood in a pixel, so as to design certainty function and structural-adaptive applicability function. Experimental results prove that our proposed algorithm can provide improved denoising effect in the output image and achieve a state-of-art optical resolution in the image edges and detailed features.

Yu Liao, MaoSheng Tian, Li Guo

An Improved Method Research of SAR Images Thresholding Segmentation

Aiming at the characteristics of SAR image and the defect of two-dimensional histogram oblique segmentation, by redefining the two-dimensional histogram, changing the thresholding range, and introducing within-class variance to redefine the thresholding function, we segregate the target area from background area precisely and improve the quality of image segmentation. So it achieves a better segmentation performance. The edge information of the SAR images can be obtained precisely and the interference of the background will be greatly reduced.

Hongyu Zhao, Qingping Wang, Weiwei Wu, Naichang Yuan

Efficient Self-Adaptive Image Steganography Scheme Based on Iterative Blending and Integer Wavelet Transform

In order to improve the capacity of image steganography scheme, a novel self-adaptive image steganography scheme, taking advantages of iterative blending and integer wavelet transform (IWT), is proposed in this chapter. The employment of IWT resolves the problems of boundary difference and rounding difference of image steganography scheme based on traditional wavelet transform. Moreover, human visual model (HVS) is adopted to effectively make a trade-off between imperceptibility and robustness. Experimental results demonstrate that the proposed scheme has excellent properties of invisibility and robustness, furthermore, the adoption of iterative blending technique highly improves the hiding capacity of the proposed scheme.

Peipei Liu, Chuan Chen, Liangquan Ge, Yaoyao Luo

An Adaptive Image-Hiding Algorithm Based on Optimal LSBs Substitution

In order to improve the quality of the embedding result and the hiding capacity of the image, this chapter presents a method of information hiding algorithm based on optimal LSBs substitution and image visual perception. By the hard c-means clustering analysis and according to the characteristics of human vision sensitivity, an optimal pixel adjustment process is applied to the scrambling technology to improve the quality of embedding result. In addition, the spatiotemporal chaos mapping can be used to solve the problem that the hiding algorithm cannot provide a way of protecting the secret information. The initial parameters of the spatiotemporal chaos mapping can act as the private keys, which can provide larger key space. Experimental results showed the proposed algorithm can make a great improvement in both the imperceptibility and the quality of the cover-image.

Chen Gui-qiang, Zhang Qi-lin, Wang Huan-wen, Wang Li-qin

Detecting Motion Regions Using Statistic Parameters

Background subtraction has become a popular method for video-based motion detection. In this chapter, we present a novel statistic parametric model by doing statistical analysis for history samples, incorporating the parameters of the sample number forming the models, the sampling time center and the last time point, which are ignored by existing background models. With these parameters, the model can be updated in time and accurately. The experimental results show that the presented model can suppress false detections from tail phenomenon, shadows, illumination change, repetitive motion, cluttered areas, and so on.

Yun Gao, Hao Zhou, Xuejie Zhang

Improved Compressed Sensing Image Reconstruction Method

In order to improve the accuracy of noise image reconstruction method, an algorithm which is based on compressed sensing theory’s Gradient Projection for Sparse Reconstruction is proposed. The image signals are sparse by introducing the wavelet theory. With the Gaussian random matrix, the images signals are been measured, and then the Gradient Projection for Sparse Reconstruction is used to reconstruct image. Experiment results show that the method improves the image reconstruction accuracy and the image reconstruction quality as much as possible compared with the traditional MALLAT reconstruction algorithm. And research of compressed sensing image reconstruction method can effectively solve the image reconstruction accuracy question.

Yan Haixia, Liu Yanjun

Image and Video Processing (2)

Frontmatter

Image Specification Based on Multimodal Gaussian-Like Function

In order to solve problems such as histogram equalization’s uncontrollability, histogram specification’s subjectivity, and trial and error, a new image enhancement algorithm using histogram specification based on multimodal Gaussian-like normal distribution function is proposed in this chapter. The proposed algorithm calculates the average gray value and contrast of original image and uses these two parameters to obtain all means and standard deviations of multimodal Gaussian-like normal distribution function and then it specifies the histogram of the image processed with this function. In addition, by introducing the gains of Gaussian peaks, the wave shape of this function mentioned above can be adjusted. So with multimodal Gaussian-like normal function as histogram transformation model, the histogram of image processed is constrained into the specified shape. Finally, the experimental results show the superiority of the proposed algorithm compared with some existing algorithms such as traditional equalization, equalization based on bimodal Gaussian-like distribution, etc. It also has many advantages over other image enhancement methods such as low computational complexity, high efficiency, and no manual intervention. Moreover, it can be easily controlled. The algorithm can not only selectively enhance the image local contrast but also improve the average gray value; so the processed image looks more realistic, being rich in layers and details.

Jun Kong, Min Jiang, A. Halidan, R. Maimaiti

An Adaptive Lossless Video Compression Algorithm Based on Video Flatness

This chapter proposes an adaptive lossless video compression algorithm based on video flatness, which combines JPEG-LS (Joint Photographic Experts Group Lossless) with the difference of adjacent frames. Since the image flatness is taken into consideration, the algorithm can adaptively choose the data from frame difference or the original one, and the compression ratio is improved. The scheme of the algorithm is illustrated in this chapter. Then contrasting experiments are used to evaluate the accuracy and efficiency of the proposed algorithm. The proposed algorithm based on video flatness has good effect on those videos whose background changes slowly and thus provides a new method for lossless video compression.

Lei Wang, Wei Zhu, Peng Chen, Yayu Zheng

Texture Data Compression of 3D Face Based on Multi-color Simultaneous Algebra

To resolve texture data of the 3D face data capacity storage consumption of larger, computationally intensive problems, this chapter presents a 3D face color texture data compression method, which is constructing a GHA (General Hebb Algorithm) neural network within the framework of the Young–Helmholtz three-color simultaneous algebra, constructing the corresponding network structure and learning algorithm, extracting the principal component of a large amount of the color texture data, and storing them in the form of weight matrix to be used for the texture data compression. The experimental results show that proposed method not only has good PSNR value but also has good generalization ability. The weight matrix is able to compress the texture data of different person faces data with different postures. It has compression universality.

Lijun Ding

Face Detection Technology Research Based on AdaBoost Algorithm and Haar Features

Face detection technology is an important branch of digital video processing technology. This chapter proposed a face detection technology based on haar features and AdaBoost algorithm. In this chapter, haar features, integral image, AdaBoost algorithm, and cascade classifier were introduced, features were extracted by haar features, and integral image and AdaBoost algorithm were used to select suitable haar features for facial features; classifier was the classifier finally constructed and used to face detection. It was found out that the common features (a small amount of haar features) play an important role in face detection. To verify this method, experiments on both static pictures and video stream were conducted. Experimental results showed that the model of haar features and AdaBoost algorithm face detection technology had high detection accuracy with more hardware cost while a small number of common features would reduce hardware cost and had greater significance in real-time face detection.

Geng-hui Wang, Ji-cai Deng, Dong-bo Zhou

MRI Brain Segmentation Based on a Three-Dimensional Markov Random Field Model

In this chapter, a segmentation method of Magnetic Resonance Images (MRIs) of brain based on an improved three-dimensional Markov Random Field (3D-MRF) model is proposed. Compared with 3D images, 2D images do not contain information among slices. The 3D-MRF model, proposed in this chapter, can make full use of the information among slices of 3D medical images. For the first case, to reduce the computational burden of 3D-MRF method, 3D K-means clustering is used to obtain initial segmentation results. In the next case, sample training method is used to estimate parameters and the optimal solution, under maximum a posteriori (MAP) criterion, is achieved by Iterated Conditional Modes (ICM) algorithm. The experimental results show that the proposed 3D-MRF model can effectively use information among slices and the results are more robust and accurate than traditional segmentation methods such as fuzzy C-means (FCM) algorithm and K-means algorithm.

Liang Li, Mei Xie, Jingjing Gao, Xingming Yue

Analysis of Correlation Registration Algorithms in the Observation of Solar Magnetic Field

This study compared and analyzed the image registration algorithms of phase correlation and cross-correlation for obtaining high SNR images. By processing both the simulated and measured images, five statistics to evaluate the results of the processing were chosen, which are the mean and variance of the difference images, the maximum correlation value of registration images, entropy of accumulated images, and energy of the magnetic images. It was concluded that the phase correlation algorithm was more sensitive to noise than cross-correlation, and the cross-correlation algorithm was more suitable for the real-time processing of solar magnetic field images.

Jie Chen, Kaifan Ji, Hui Deng, Song Feng

Iterated Image Restoration in the Closed Underwater Environment

In order to restore image from poor visibility caused by more backscatter and signal attenuation in the closed underwater environment, an iterative algorithm is used in this study. By constructing three models of the angle between underwater light and camera, the iterative method can effectually recover underwater scene, filtering the backscattering and a lot of unidentifiable noise. For illustration, contrasting regularization with iteration is utilized to show the validity of the latter in restoring image. Empirical results showed that the iterative algorithm can rebuild image, improve the sharpness of the image, and conserve target information. The recovery-measure-based iteration algorithm can validly inhibit different kinds of underwater disturbance, and thus the problems of underwater image restoration such as backscattering and signal attenuation can be solved.

Xiangchuan Min, Shaosheng Fan

Hyperspectral Images Target Recognition Using Projection Pursuit

In order to solve the recognition problem of the specific target, a hyperspectral target recognition method using minimum noise fraction (MNF) and projection pursuit was used. Firstly, MNF was used to calculate the intrinsic dimension as well as image denoising. Then, using spectral information divergence (SID) as the projection index, remove the background and extract the spectral curve via adaptive threshold of the value of the projection index. When calculating each projection index, we used a simplified approach to maximize the projection index, which does not require an optimization algorithm. It searches for a solution by obtaining a set of candidate projections from the data and choosing the one with the highest projection index. Finally, identify the target and its location using the spectral angle mapping method. Through a series of hyperspectral images experiments, the results show that the MNF image preprocessing can make the projections better and reduce the computational effectively. Remove the background using adaptive threshold of the projection index quickly and efficiently. The method can not only reduce the images noise more effectively but also extract endmember and identify the target quickly, reliably, and fastly.

Xiaoping Du, Jie Sun, Lurui Xia

Automatic Image Annotation Based on Multi-scale Salient Region

Automatic image annotation is a challenging problem in image understanding areas. The existing models directly extract visual features from segmented image regions. Since segmented image regions may still have multi-objects, the extractive visual features may not effectively describe corresponding regions. In order to overcome the above problems, an image annotation model based on multi-scale salient region is proposed. In this model, first, each image is segmented by using multi-scale grid-based segmentation method. Second, global contrast-based method is used to extract the saliency maps from each image region. Third, visual features are extracted from each salient region. Finally, multi-scale visual features of image regions are fused and applied to automatic image annotation. Our model can improve the object descriptions of images and image regions. Experimental results conducted on Corel 5K datasets verify the effectiveness of proposed model.

Xiao Ke, Guolong Chen

Implementation of Parallel Computing FAST Algorithm on Mobile GPU

Corner detection is an extremely important technique in image recognition, which is widely employed in various applications for image recognition. With the widespread use of mobile devices, image recognition techniques are frequently applied in such devices. However, the hardware resource of smartphones is lacking and restricted; it is a difficult task to apply the techniques of corner detection smoothly in these devices. To enhance the computational speed, the FAST corner detection algorithm is implemented with parallel computing of GPU in mobile devices. In the experiments, the computational speed of the FAST corner detection algorithm increases 24 times after using GPU parallel computing. Compared with the widely known SURF algorithm, which is computed with mobile CPU only, the proposed technique in this study is 468 times faster than SURF algorithm.

Chien-Hsing Chou, Peter Liu, TaiYi Wu, YiHsiang Chien, YuXiang Zhao

Signal Processing Theory and Applications

Frontmatter

Realization of Vehicle SINS Four-Position Alignment Method Based on FPGA and DSP

Initial alignment is one of the important factors to affect the accuracy of strapdown inertial navigation (SINS). SINS observability analysis indicates that fixed position SINS is not completely observable, and the multiple position alignment method can make SINS completely observable by changing the IMU location. In addition, the multiple position alignment method can improve the precision of initial alignment. In this chapter, the four-position alignment method was analyzed, and SINS four-position alignment system was realized based on FPGA and DSP. The experiment of a certain vehicle indicated that this proposed four-position alignment system is feasible.

Meng Wu, Xiaqing Tang, Xiangyuan Huang

INS/GNS Integrated Navigation on Small Area

In order to reduce the navigational errors caused by the model factors and achieve high-precision navigation in small-scale areas, the original Earth’s main magnetic field model created by the dipole is replaced by rectangular harmonic model as the INS/GNS integrated navigation system observation equation. At the same time, with the complex magnetic interference in the actual environment and its unknown statistical properties, to avoid calculating the Jacobean matrix in literalizing the observation equation, the UKF algorithm is adopted in the design of a nonlinear time-varying noise estimator to reduce magnetic interference and improve the accuracy of navigation. The simulation results show that the algorithm greatly improves the accuracy of the integrated navigation. It can be used in noisy environments.

Jing-li Huang, Guo-rong Zhao

Analysis About the Impacts of the Theodolites Distribution to the Two Stations Intersection Measurement

Firstly, this chapter introduces the commonly used L formula and its improved intersection measurement in the range. In order to analyze the impacts of the theodolites distribution on the two stations’ intersection measurement, four stations and an ideal track are set in this chapter. Through the simulation analysis, two cases of the two stations’ intersection measurement errors are obtained: one case is when the two stations are located on the same side of the track, and the other case is when the two stations are located on the opposite sides. Moreover, the cause of the different error cases is analyzed and detailed comparison between them is made. All the observations above provide technical support to the reliability of real-time data analysis and the outside measurement data post-processing analysis, which is of great significance to the theodolites distribution in the project.

XinWei Liu, YunAn Hu, Liang Liu

The Research on the Jam Blind Separation of Misalignment Signal

In view of noncooperative communication occasions, the separation of the single channel misalignment mixed MSK signals was researched. This research is based on derivation of cyclic spectrum. A frequency shift exists in the misalignment signal, and simultaneously, the mixing signals are transmitted on the channel to generate frequency deviation. BSS makes use of both the deviations to separate signals. The expression of overlap percentage is derived. The simulation results show that the frequency shift is utilized to separate misalignment signal, and the cyclic spectrum estimation is more suitable for the parameter estimation in the blind separation of the alignment signal.

Shuang Pan, Ruihua Zhang, Gang Wu, Yuqiang Wu

A Fast-Study Model of Aircraft Magnetic Field Based on Two Flights Data

In order to reduce the study time in magnetic survey, a fast-study model of aircraft magnetic field was put forward here on the basis of the small signal model proposed by S.H. Bickel. The fast model uses the original induced and eddy-current parameters to recalculate the new permanent parameters. It can reduce the study flight amount from two to four; so the study time can be reduced from about 4 to 8 min at one time. Finally, a simulation was conducted to compare the compensation effects between the small signal model and the fast-study model. The result showed that the compensation effect of fast model was still very close to the effect of small signal model. So the new model can be used in magnetic survey if time is limited.

Jian-Jun Zhou, Chun-Sheng Lin, Ying-Chung Huan

Optimal Frequency Band Selection Based on Filter Banks and Wavelet Packet Decomposition in Multi-class Brain–Computer Interfaces

To address the problem of low system recognition rate in multi-class brain–computer interface (BCI), many ideas have been proposed. Among them frequency optimization is a good option because the performance of BCI systems depends largely on the operational frequency band of electroencephalography (EEG) signals. In this chapter, feature selection method was utilized to select frequency bands for classification in multi-class BCI systems. The procedures of the proposed algorithm are as follows: Firstly, all single-trial EEG signals are divided into some subband signals by two different methods. One is wavelet packet decomposition and the other is filter bank based on coefficient decimation. Secondly, a multi-class common spatial pattern algorithm based on approximate joint diagonalization is used to extract features of EEG signals on each subband. Finally, optimal subband features are selected for classification. In offline analysis, the proposed method yielded relatively better cross-validated classification accuracies.

Qingguo Wei, Bin Wan, Zongwu Lu

Channel Reduction by Cultural-Based Multi-objective Particle Swarm Optimization Based on Filter Bank in Brain–Computer Interfaces

Applying many electrodes is undesirable for real-life brain–computer interface (BCI) application since the recording preparation can be troublesome and time-consuming. This chapter presented a novel channel selection method, named cultural-based multi-objective particle swarm optimization (CMOPSO) based on filter bank, which introduced a cultural framework to adapt the personalized flight parameters of the mutated particles. A filter bank was designed using a coefficient decimation (CD) technology. The broad frequency band (8–30 Hz) is divided into ten subbands with width 4 Hz and overlapping 2 Hz, and the channel selection algorithm was applied to each subband. The optimal channels were chosen from the best channels derived from each subband. The algorithm was tested on five four-class data sets and the experimental results showed that the approach outperforms the broad band approach in selecting a smaller subset of channels without the sacrifice of classification accuracy.

Qingguo Wei, Yanmei Wang, Zongwu Lu

Positioning of Singular Point of Motor Vibration Signal Based on Wavelet Transform

In order to position the singular points and irregular transient parts of the motor vibration signal, the principle of signal singularity detection based on wavelet transformation modulus maximum is presented in this chapter. And the multiplying detail signal multiplication method is adopted according to the signal singularity Lipschitz exponent and modulus maximum scale transform characteristics. Simulation signal and vibration signal experiment results show that the wavelet can accurately analyze the time distortion occurs. And by using the detail signal multiplication approach, the signals are enhanced while suppressing the noise, so as to achieve the accurate positioning of the singular points of the motor vibration signal.

Dongdi Chen, Jin Zhao, Zhongyu Shen

Apparent Longitudinal Conductivity Interpretation Method in Transient Electromagnetic Technique

According to the principle of equivalent conductive plane, this chapter discusses apparent longitudinal conductivity in layered media, describes its advantages, uses numerical methods (i.e., central difference algorithm) to calculate the derivative of transient response in forward processing, and uses spline interpolation method instead of solving the inverse function in traditional sense in acquiring the key value M to simplify the calculation. When verifying the effectiveness of apparent longitudinal conductivity interpretation, the forward data of typical geoelectric model of in H-type Layer 3 and HK-type Layer 4 are used to inspect. The results show that the curves of apparent longitudinal conductance can distinguish electrical layers clearly, and can also indicate the magnitude of conductance of layers, so as to achieve a good explanation.

Di Fan, Yuduo Wang

EEG Filtering Based on Machine Learning Simulation Design Analysis

The pretreatment of collected electroencephalogram (EEG) signals is quite important in processing EEG signals. By adopting the knowledge of signal analysis and processing based on Matlab platform, the impact of different wavelet basis functions on the decomposition and reconstruction of EEG signals is simulated. Then EEG signals are decomposed and reconstructed in a five-layer multi-scale way by using db5 wavelet basis function, and the vibration of the signals is simulated. By comparing the simulation results of denoising under different thresholds with that under low-pass filters, the results of specific frequency bands are analyzed. The research shows that in the process of denoising EEG signals, wavelet analysis can extract EEG micro signals effectively, and thus it has important value in the practical use of EEG in broader fields.

Xin Xu, Bin Lv, Yanting Hu, Yun Zhou, Jiansheng Wu

Radar and Array Signal Processing

Frontmatter

Robust Estimation for Ship-Borne Radar Detecting Biases

An important prerequisite for successful multi-radar integration is that the data from the reporting radars are transformed to a common reference frame which is free of systematic or registration errors. According to the ship-borne radar data processing, the types of bias are divided into four main categories: radar measurement biases, ship-position biases, attitude biases, and baseline transform biases. In this chapter, we present an algorithm which uses detecting data for estimation of equivalent biases. Our approach is unique for two reasons. First, we explicitly avoid the individual biases and instead use equivalent biases modeling the four main class biases, which leads to a highly nonlinear bias model that contains 12 unknown parameters. Then, we use the singular value decomposition (SVD) within least-squares estimator to automatically handle the issue of parameter observability. Finally, according to two different simulation scenes, we demonstrate that our algorithm can improve track accuracy, especially for ship-borne radar.

Jiang-Huai Pan, Jia-Zhou He

Measurement of Target’s Motion Parameter for CW Radar

This study aims to accurately estimate the target’s motion parameter for constant wave (CW) radar and to reduce the computing complexity. Firstly, the echo signal of CW radar is separated into two sine signals by a novel signal transform, and the frequency of each sine signal is proportional to one of motion parameter for target; then these motion parameters are estimated by the frequency estimation algorithm which is based on chirp-z transform and Fast Fourier Transform (FFT). The statistical character of this method is analyzed and the mean square error of parameter estimation is deduced. The simulation result shows that the proposed method has a low computational cost and high performance close to Cramer-Rao lower bound (CRLB).

Baojun Zhang, Weiting Feng

Design and Implementation of Micro-broadband Radar Signal Source

This chapter provides a design of micro-broadband radar signal source based on direct digital frequency synthesis technology. This micro-broadband radar signal source is composed of baseband signal source and frequency multiplier chain. Direct Digital Synthesis (DDS) chip AD9858 was used in the baseband signal source. A FPGA chip was employed to load DDS control words to create 200MHz ± 50MHz baseband signal. Multiplier chain achieved up-conversion and frequency doubling of baseband signal, and output 1.5GHz + 400MHz broadband radar Linear Frequency Modulated (LFM) signal. Oscilloscope and spectrum analyzer measurements results showed that the quality of LFM signal met the design requirements.

Yafang Yin, Yanna Liao

A Nonlinearity Measurement Method for Frequency-Modulated Continuous Wave Synthetic Aperture Radar Imaging

One crucial limiting factor to the use of frequency-modulated continuous wave synthetic aperture radar (FMCW SAR) sensors is the well-known presence of frequency nonlinearities in the transmitted signal, which highly deteriorates the range resolution because of the pair-echo effect. By analyzing the FMCW SAR nonlinear signal model, a novel nonlinearity measurement method is proposed based on the time-shift characteristic of the Fourier transform. With the accurate estimation of the nonlinearity term, the modified frequency scaling algorithm is applied with nonlinearity correction to complete the imaging process. The validity of the proposed algorithm is demonstrated with multi-point targets simulation, confirming its superiority in terms of resolution, PSLR, ISLR, and final focused images.

Wen Yu, Siwei Zhao, Xiaoquan Song, Yueqing Gao

A Simulation Model of the Positioning Accuracy in the Multi-radar Foreign Object Debris Detection System

This chapter illustrates the method using multi-radar network for improving the positioning accuracy in Foreign Object Debris (FOD) radar detection system. To achieve the accuracy improvement, two or even more radars are applied to detect the same target to decrease the minimum detection zone and improve the positioning accuracy. Firstly, a mathematical model for the detection situation in FOD radar network is built, and thus this issue is reduced to an analytic geometry problem. Secondly, in analyzing the model, the minimum detection zone is found, whose largest feature size is calculated as the positioning accuracy. The simulation results of the positioning accuracy to the designated detection zone in double-radar and triple-radar systems are presented in figures. Finally, the conclusion that the positioning accuracy of the multi-radar FOD detection system can be improved with the increasing number of the radars is verified. After modifying the simulation algorithm, this data fusion method can be embedded in the hardware platform to improve the positioning accuracy of the multi-radar FOD detection system.

Feng Jin, Guolong Wan, Qiong Wang, Jin Zhang

Direction of Arrival Estimation of Two Wide-Band Sources with Small Array Based on Beam-Space Coherent Signal-Subspace Method

In order to obtain directions of arrival (DOA) of two wide-band sources effectively, with a small size four-element planar cross array, the beam-space coherent signal-subspace method (BSCSM) applied to the orientation of wide-band sources was studied, and its performance was analyzed. Measured helicopter noise was used to simulate output of array elements as wide-band sources, which contains the certain directions of target arrival. The BSCSM and CSM (coherent signal-subspace method) were employed respectively to estimate sources’ DOAs. The performance of BSCSM was compared with CSM using computer simulation. The simulation results show that BSCSM provides a better performance than CSM in the passive acoustic direction estimate for two far-field wide-band sources with small size four-element planar cross array.

Xiaojuan Bai, Ya’an Li, Wei Zhang, Fengxue Liu, Daiqiang Cao

Using Aero-Acoustic Vector Sensor for Acoustic Measurement and Target Direction Finding

In order to estimate the direction of the ground target intruded upon the special region, the acoustic system composed of aero-acoustic vector sensor (AVS) is designed, and a new method of direction finding based on estimation of the sound intensity is proposed in this chapter. By utilizing AVS to measure acoustic pressure as well as the acoustic particle velocity, the sound intensity is estimated, and the sound intensity represents the direction of the target or propagating part of an acoustic field thus indicating the direction of arrival (DOA) of a received signal. Simulating with the noise signal radiated from the real target, the results show that the algorithm can achieve direction estimation precision of 2.5° when the size of AVS is 0.28 m and signal noise ratio (SNR) 0 dB. From experimental research on sound intensity of the AVS, the results indicate that the method can reach a high precision; the maximum standard deviation (STD) is <3°. The technique studied in the chapter could be absolutely used to estimate the direction of the ground target and put forward a new approach to acoustic detection of the low altitude target such as helicopters, pilotless aircrafts, and so on.

Zongyi Cai, Xuezhong Xu, Mingrong Dong

Design of Radar Electromagnetic Environment Simulator

A radar electromagnetic environment simulator is designed to generate echo signals of targets, active jamming, and clutters according to specified parameters and provide an electromagnetic environment with stated tactics background for radar operators. By analyzing the characteristics of radar electromagnetic environment and the form of echo signal, simulation of electromagnetic environment was reduced to control echo signal’s power, delay time, and Doppler frequency. Then the hardware implementation scheme including main control computer, digital signal processor (DSP), and field programmable gate array (FPGA) is put forward to accomplish setup of electromagnetic environment parameters, communication with radar, calculation of radar working state, and generation of analog signals. At last, the implemented system was connected to actual radar for experiments. The results prove that this system can generate echo signals consisting of targets, jamming, and clutters for the radar and simulate radar’s electromagnetic environment with specified patterns, which effectively help operators’ training.

Heming Wang, Wenlong Lu, Chuan Sheng

Antennas, Modulation, Coding, and Channel Analysis

Frontmatter

Gauss White Noise in Digital Frequency Modulation Scheme

This chapter introduces the scheme about how to generate the band-limited Gauss white noise digital FM signal scheme. Firstly, generate pseudorandom sequence, then transform the pseudorandom from the Uniform distribution to the Gauss distribution, then do low-pass filtering. Finally, realize digital FM processing by the method of direct digital frequency synthesis (DDS). The simulation results show that the scheme can generate effective Gauss white noise signal.

Xu Song, DaYong Liu, Zhe Chen

A Bandwidth Allocation Strategy Based on Multirate Sampling Method in Networked Control System

Considering the resource constraint, a bandwidth allocation strategy with multirate sampling method is proposed to achieve the control and scheduling codesign of networked control system (NCS). The bandwidth allocation strategy integrates static scheduling method with dynamic scheduling method. Final bandwidth of each closed loop is determined by three steps. Firstly, the basic sampling period is selected based on the maximum available bandwidth of network. Then, the initial bandwidth allocation method is given on the basis of the sampling period which is determined by the different characteristics of each closed loop and the central bandwidth can be obtained in this step. At last, the final bandwidth can also be adjusted dynamically on the basis of the state change of each plant. In order to verify the validity of this bandwidth allocation strategy, the stability of control system and the bandwidth utilization of network system are shown through simulation experiments.

Zhiwen Wang, Hongtao Sun

Train–Ground Signal Credible Transmission Platform for Multi-rate LDPC Code

LDPC (low-density parity-check codes) which are a class of error-correcting codes based on the linear block codes of the sparse check matrix with a wide range of applications are close to the Shannon limit up to now. And the related reports are not found in the application of train–ground wireless transmission system. This chapter presents that the LDPC which are in excellent performance apply into the part of the channel code in this kind of system in order to improve safety and reliability and have a far profound significance and a high value of practical application. In this chapter, a class of multi-rate LDPC codes and its simplified decoding algorithms are presented, which apply high level architecture to the train–ground wireless communication system’s simulation and testing platform. By means of simulation of platform, we evaluate the train–ground system BER performance, the performance of joint source channel coding, and sequential decoding using turbo-decoding message-passing (TDMP) algorithm in AWGN channel is compared, and a lower error rate is obtained. The LDPC-based train–ground system attains an order of magnitude improvement in throughput.

Lan Chen, Jian Chen, Guochun Wan

A Nonlinear Distortion Compensation Algorithm for 32APSK Modulation over Satellite Channels

It is essential to use high power amplifiers (HPA) on satellites because of the large attenuation during data transmission over satellite channels. The nonlinear characteristics of HPA will introduce spectral regrowth and constellation warping. As a countermeasure, many designers prefer to utilize the data pre-distortion technology implemented at the baseband as the simplicity of digital signal process realization. In this chapter, a nonlinearity distortion compensation algorithm, employing high order amplitude phase shift keying modulation scheme, combining with simplified data pre-distorter at the transmitter and nonlinear blind equalizer at the receiver is investigated to mitigate the nonlinear distortion. Matlab simulation results show that the nonlinear distortion of HPA is significantly decreased by adopting the joint scheme, and the computational complexity is greatly relieved.

Maoqiang Yang, Daoxing Guo, Kun Zhao, Lu Lu

Synchronization for Uncertain Chaotic Systems with Channel Noise and Chaos-based Secure Communications

In order to deal with the problems of chaotic synchronization and chaos-based secure communication for uncertain chaotic systems with channel noise, a robust sliding mode observer is constructed to synchronize the chaotic system which is regarded as the transmitter. By introducing an augmented vector, an augmented system is formed, and the channel noise of chaotic system is estimated by the robust sliding mode observer. Then, a first-order robust differentiator is considered to exactly estimate the derivative of drive signal. Based on the estimated states and the derivative of drive signal, a recovery method which can recover the information signal is proposed. For illustration, a numerical simulation is given to show the effectiveness of the proposed methods. The simulation results show that the receiver which is the combination of the robust sliding mode observer and the first-order differentiator can not only synchronize the transmitter but also recover the information signal. The proposed method can effectively achieve synchronization and information recovery when the chaotic system with channel noise is used as the transmitter.

Junqi Yang, Fanglai Zhu

Novel Compound Planar Spiral Antenna

The tradition compound planar spiral antenna cannot get good performance at low frequency by effects of the terminal reflection. In order to solve this problem, a novel compound planar spiral antenna by adding a peripheral structure is presented. Favorable miniaturization and wideband properties are shown in the simulation and measurement. The axial ratio of proposed antenna is less than 3 dB, and the gain is greater than 1dBi between 0.3 and 3.5 GHz. The performance of this antenna at the low frequency is improved by comparison with the typical compound planar spiral antenna without the peripheral structure.

Mingqing Chen, Gaofeng Wang, Shuhua Zhou

A Broadband Portable Three-Wire Antenna for Low-Power Vertical-Incidence Ionosonde

At present, almost all of the ionospheric sounders for the HF-band around the world are fixed. As a result the areas of sounding are restricted and the equipment cannot be fully exploited. After studying the design of the ionospheric vertical sounding antenna and the standard of parameter setting, a portable vertical sounding antenna based on portable single station ionospheric sounding system is designed that can be spanned easily. Compared to the traditional delta antenna and rhombic antenna, this one has the advantage of lower antenna height, smaller occupied area, smaller VSWR and better radiation performance, which achieves the broadband impedance and antenna pattern. The result suggests that this one is better than a conventional portable ionospheric VI sounding antenna.

Bo Bai, Ming Yao

Wireless Communication and Mobile Computing (1)

Frontmatter

Mobile Cloud Forwarding Service in Delay Tolerant Networks

Mobile data access is suffering from the curse of the computationally enhanced increasing of smart phones, which overloads the 3G network. Offloading mobile traffic through Delay Tolerant Networks (DTN) is an efficient way. Due to the uncertainty of transmission opportunity, routing algorithms in DTN often need nodes serving as relays for others to carry and forward messages. In this chapter, we propose the concept of cloud forwarding service. The service provider has certain mobile devices (cloud resources), and it uses these resources to help the source to carry and forward messages by charging certain reward. If the source requests help from the provider, it can transmit message to the destination quickly, but it has to pay certain reward. On the other hand, if the destination obtains message sooner, the source may receive more reward. This chapter proposes a theoretical framework to evaluate the total reward that the source obtains. Simulations based on both synthetic and real motion traces show the accuracy of our model.

Yahui Wu, Su Deng, Hongbin Huang

The Design of Passive Intermodulation Test System Applied in LTE 2600

For the purpose of measuring the passive intermodulation (PIM) products caused by the nonlinearities of passive devices, this chapter proposes a design of PIM test system which can be applied in long-term evolution (LTE) 2600. By reflecting the combined signals generated by two power amplifiers, the test system is able to capture and analyze PIM products accurately. Furthermore, the test system is composed of transmitter, receiver, and control system. By adopting advanced RISC machines11 (ARM11)—S3C6410, the test system achieves an excellent performance. Finally, experimental results show that the test system has good reliability and accuracy.

Gong Lin, Chenghua Wang, Wenjue You, Yunqiang Wan

Adaptive Modulation with Antenna Selection and Imperfect Feedback in Rayleigh Fading Channel

Based on imperfect channel feedback information, the performance of multi-input multi-output (MIMO) systems with adaptive MQAM and antenna selection (AS) in Rayleigh fading channel is presented. Subject to a target bit error rate (BER) constraint, the switching thresholds for adaptive modulation (AM) are provided. The probability density function of the effective signal to noise ratio is derived. According to these results, closed-form expressions of the spectrum efficiency (SE) and average BER of the system with delayed feedback are respectively derived. These theoretical expressions can provide good performance evaluation for AM-MIMO system with AS. Simulation results for SE and BER are in good agreement with the theoretical analysis. The results show that the AM-MIMO system with antenna selection provides better SE than that with space–time coding and has BER performance degradation for imperfect feedback.

Xiangbin Yu, Lengchi Cao, Wenting Tan, Xin Yin, Xiaomin Chen

An Improved Double Iterate Equalize Algorithm for Continuous Phase Modulation

The high-speed wireless data transmission business is growing rapidly, but the high-speed data transmission and high spectral efficiency application system have many problems, such as the divergence of the channel will lead to the serious inter symbol interference (ISI). It is therefore necessary to use equalizer to reduce the impact of ISI. In the condition of large channel memory length, when modulating, its complexity may not be accepted. Therefore, it may use a sub-prime but low complexity turbo equalize receiver. Its main idea is separating the channel equalizer, continuous phase modulation (CPM), and the channel decoded operation. It will make double iteration between the equalizer and the demodulator. Experimental simulation indicates that the double iteration algorithm overcomes the shortcoming under the adverse conditions greatly, for example, the channel memory length is too large or there are too many super grid states.

Yi Yan

A Dual Channel Reservation MAC Protocol for Mobile Ad Hoc Networks

To resolve hidden terminal and exposed terminal problems and improve the probability of simultaneous data packet transmissions for multihop mobile ad hoc networks (MANETs), we propose a novel dual channel reservation (DCR) medium access control (MAC) protocol. The protocol achieves simultaneous collision-free contention reservation access and data packet transmission and optimal load balance between the packet transmissions on reservation channel (RCH) and traffic channel (TCH) by appropriately adjusting the data rates of the RCH and TCH and guaranteeing the same interval of reservation slot on the RCH as that of data packet transmission slot on the TCH. Finally, simulation results show that in the presence of the same total data rate, the DCR protocol obviously outperforms the IEEE 802.11 distribution coordination function (DCF) protocol in terms of multiple access performance.

Duoying Zhang, Wenqiang Zhang, Kai Liu

An Improved K-Best MIMO Detection Algorithm for Parallel Programmable Baseband Architecture

In MIMO-OFDM systems with multiple layers spatial multiplexing and high-order QAM, efficient MIMO detection is very significant for receiver design. Among current MIMO detection algorithms, K-Best is a prevailing algorithm with fixable balance between performance and complexity. However, the current K-Best and its varieties are not suitable for parallel programmable baseband architecture, such as DSP with VLIW, SIMD, or vector processing features. In this chapter, an improved K-Best detection algorithm is proposed, and an efficient soft-output algorithm is designed. Simulation results show that its performance is near to general K-Best with lowered time complexity, especially under high SNR. Using this algorithm, the system throughput can be increased in times.

Cheng Tan, Yifei Zhao, Chunhui Zhou, Yunzhou Li

A New Synchronized Multi-interface MAC Protocol for Multi-hop Wireless Mesh Networks

Multichannel MAC protocol (MMAC) was proposed by So et al. It divides time into beacon periods and consists of an announcement traffic information message (ATIM) phase and a data phase (So et al. Proceedings of 5th ACM international symposium on Mobile ad hoc networking and computing(Mobihoc’04),2006). Nodes negotiate during the ATIM phase on a common channel and transmit data in data phase on multiple channels. But one negotiation window in each beacon period limits the networks performance in multi-hop scenario which plays the main role in Wireless mesh networks (WMNs). In this chapter, researchers propose Synchronized Multi-Interface MAC protocol (SMIMAC), in which the ATIM phase is divided into multiple short windows. And each of them is followed by a short data window. Without increasing the sum of negotiations time, multiple but short consultation windows can provide negotiation opportunities for those nodes which fail to consult before and those nodes which are away from the sender when they have packets to transmit. The simulation results show that the scheme achieves seven time higher aggregate network throughput and average packet delay reduced to 32 % of MMAC in multi-hop scenario.

Hongjiang Lei, Zhi Ren, Jun Huang, Chao Gao, Yongcai Guo

Wireless Communication and Mobile Computing (2)

Frontmatter

Optimizing Polyphase Coded Signals for MIMO Radar

Orthogonal signals are usually required to be transmitted for Multi-Input Multi-Output (MIMO) radar. A new set of polyphase codes is obtained with very low aperiodic autocorrelation sidelobe and cross-correlation levels, as well as good Doppler shift resilience. An Adaptive Clonal Selection (ACS) algorithm is proposed to optimize the codes, on which Doppler shifts are imposed. Numerical simulation and results show the superior correlation and Doppler performance comparing with some well-known codes.

Jin Yang, Lei Nie, Weidong Jiang, Zhaowen Zhuang

Implementation and Performance Analysis of HARQ in 3GPP LTE System-Level Simulation

The standardization of 3GPP LTE/LTE-A is in process and related research is also very popular. However, when CoMP has been raised in 3GPP #bis 53 meeting, implementation of CoMP HARQ in LTE system-level simulation is in silence. In this chapter, we design a data structure of HARQ model in our Matlab-based LTE System-Level simulator, which is standardized in 3GPP. This data structure is an easily upgraded one that can fully upgrade to Coordinated Multi-Point (CoMP) mode in the future. A performance analysis is also given to make a comparison of Chase-Combine (CC) and Incremental Redundancy (IR).

Yuan Gao, Peng Xue, Yi Li, Hongyi Yu, Xianfeng Wang, Shihai Gao

A Busacker–Gowen Algorithm Based on Routing Scheme for Maximizing Throughput with Minimum Delay in WOBAN

In order to optimize throughput as well as average end-to-end delay in wireless optical broadband access network (WOBAN), a novel delay aware routing algorithm was proposed in this chapter. Routing problem in WOBAN was described as a maximum flow with the minimum cost problem in this chapter. And the proposed routing algorithm which was modified from Busacker–Gowen algorithm was implemented by means of distributing flows along with available routes properly. Simulation results showed that the proposed Busacker–Gowen Routing (BGR) algorithm enhanced the network throughput greatly at a cost of minimal delay compared with the multipaths minimum hop routing (MMHR) algorithm. More specifically, when the wireless link capacity was 20 Mbit, BGR improved throughput by about 21.6 % at the cost of 0.122 ms longer delay compared with MMHR. And when the packet arrival rate was 10Mbps, BGR improved the throughput by about 15.8 % at the cost of 0.12 ms longer delay compared with MMHR. BGR algorithm can maximize the throughput with minimal delay for the data transmission in WOBAN.

Minglei Fu, Zhenpeng Zheng, Yiluan Zhuang, Bisheng Quan, Zichun Le

The Adaptive Header Compression Algorithm of Mobile IPv6 Network

In order to solve the problems existing in the general header compression algorithms, this chapter analyzed the effects of Packet Reordering Algorithm at the receiver and the error that cannot be checked out by CRC on VJ and Twice algorithm. An adaptive header compression method for Mobile IPv6 networks was presented and the problems above can be solved. Some new controlling measures were introduced in VJ and Twice algorithm to realize more packets that can be sent when the decompression end is in good state and to make the time in which it is in bad state as short as possible. Finally a sound simulation was conducted to show the performance of the methods adopted in this study.

Jing Gu

Timing Synchronization Algorithm for DRM

The accuracy of timing synchronization is very important for multipath fading channel. In this chapter, the Timing Synchronization algorithm is proposed for DRM (Digital Radio Mondiale) via reducing the length of the relevant window and detecting the total energy value with a threshold instead of the maximum correlation peak. The proposed method is based on conventional methods utilizing CP (cyclic prefix). Simulation results show that the proposed algorithm can not only reduce the computational complexity and the amount of computation but also be effective against multipath and noise with higher accuracy than conventional methods.

Cheng Yan, Fenglin Zhang, Guoche Qin

A New Dynamic Frame Slotted ALOHA Algorithm Based on Collision Factor

In order to solve the problem of the tag collision in RFID system, this chapter presents a new dynamic frame slotted ALOHA algorithm based on collision factor according to the previous different kinds of ALOHA algorithms. By introducing the pretest groups of number and collision factor, the tag number estimating method settles the severe collision where all the slots are collided slots in a frame while most of algorithms do not resolve this problem. Simulated results on MATLAB show that the estimated number of tags with this new algorithm is accurate, and the efficiency of this new algorithm is higher than other algorithms especially on the severe collision condition. On the basis of guaranteeing the accuracy of tags estimation, the problem of severe collision that the number of empty slots and readable slot are both zero was solved by the method proposed in this chapter, which ensures high speed of identification. In all, this algorithm has good performance both when there is severe collision and under normal condition.

Chengpo Mu, Jia Song, Yuanqian Chen, Zhijie Yuan

Mobile Ad-hoc and Sensor Networks

Frontmatter

A RSU Deployment Scheme Based on Hot Spot in Vehicular Ad Hoc Networks

How to maximize the network connectivity under limited RSU deployment cost is a challenging issue in VANETs. A Road Side Units (RSUs) deployment scheme is proposed by minimizing the number of RSUs and, at the same time, maximizing the network connectivity in this chapter. Multiple RSUs are deployed along road to form a backbone link, which is placed between hot spot regions to connect the “isolated islands.” The simulation results show that our scheme can achieve better performance comparing to existing RSUs deployment schemes.

Weidong Yang, Pan Li, Hongyue Liu, Jizhao Li

A Dual-Mode MAC Protocol over Mobile Ad Hoc Networks

This chapter presents a dual-mode media access control protocol (DM-MAC) for mobile ad hoc networks, which is suitable for applications in modern cooperative air combat. DM-MAC is a hybrid access scheme that combines contention-free and contention-based protocol in a positive way. In the presence of manager node, DM-MAC works on the collision-free access mode based on TDMA mechanism, while it transforms its operation into the efficient cooperative access mode based on concurrent transmission when the manager node disappears. Simulation results showed that DM-MAC can self-adjust media access mode according to the presence or absence of manager node. In addition, DM-MAC performed better than IEEE 802.11 DCF in terms of one-hop throughput and media access delay under high traffic loads.

Cheng Luo, Lei Lei, Weiling Cai, Shengsuo Cai, Ting Zhang

Performance Analysis for Dedicated Control Channel Multichannel Protocol

In order to accurately analyze the throughput performance of dedicated control channel (DCC) multichannel protocol in the case of IEEE 802.11, the performance analysis model for DCC is proposed and mathematical normalized throughput is analyzed. On the basis of new understanding of distributed coordination function (DCF) mechanism throughput formula under the saturated conditions proposed by Giuseppe Bianchi, the throughput formula of DCC is derived. Furthermore the effect of channel rate, number of channels, and number of stations on DCC throughput performance is illustrated by simulation. Simulation results show that in the case of

T

TRSMIT

/

T

RTS/CTS

> 1, DCC normalized throughput maintains a constant value, without relationship with the number of stations. With the data rate doubled, the increase of normalized throughput is significantly reduced. In the case of two channels, the difference of normalized throughput among different data rate is small. But with the increase of number of channels, the difference of normalized throughput becomes larger.

Junrong Yan

Medium Access Control Protocol for Embedded Sensor Networks and B-MAC Design

In order to minimize idle listening and achieve collision avoidance and high channel utilization rate, B-MAC is analyzed and designed in this chapter. By analyzing and contrasting the characteristics with IEEE 802.15.4, B-MAC can rationally solve the above-mentioned problems. For illustration, B-MAC design process is put forward and implemented on MSP430 eZ430-RF2500 development tool. Empirical results show that B-MAC is more efficient with long preamble. B-MAC achieves collision avoidance and high channel utilization rate by using long preamble. Although B-MAC can minimize idle listening, it needs bidirectional communication and has low power utilization. MAC protocol is an important component in communication process. Any improvement will benefit for the future embedded sensor network communication process.

Yumin Liu

The WSN-Based Fine Agriculture Environmental Monitoring System

The fine agriculture environmental monitoring system uses the large area data acquisition technology based on wireless sensor network. It can endlessly monitor soil information all the time and provide reliable basic facts for the planting plan and field management. This system adopts hierarchical network topology, with the upper layer network using self-organization topology and the under layer network using star topology. In order to better solve the energy supply problem of the cluster-head nodes, the energy supply system based on solar energy is proposed. The experiment shows that this system is highly reliable and enjoys good expansibility and great practical value.

Xing Pan, Fengtong Pan, Yi Gao, Zheng Ma

Optical Communications

Frontmatter

A 250 Mbps Transmitter with a Resonant Cavity Light Emitting Diode for Plastic Optical Fiber Communication

For obtaining high performance and low cost, a hybrid integrated transmitter is presented for plastic optical fiber (POF) communication including a 250 Mbps driver with temperature compensation of modulation current and a bonded 650 nm resonant cavity light emitting diode (RCLED) because of their incompatible material. The driver consists of an input buffer, a pre-drive amplifier, a main driver, a temperature compensation circuit to minimize the variation in extinction ratio, and a reference voltage circuit in 0.5 μm BCD (Bipolar, CMOS, and DMOS) technology. The simulation results show that it can provide modulation current of 33 mA, −3 dB bandwidth of 176.4 MHz and the operating speed of 250 Mbps at 5 V. By using the temperature compensation circuit, the modulation current of the driver has increases from 33 mA at 15 °C to 57 mA at 78 °C. The 650 nm RCLED occupying an area of 200 μm × 200 μm is bonded to this provided driver with bonding pads. The transmitter produces the maximal optical power of −1.5 dBm.

Xiaofeng Shi, Xiang Cheng, Jifang Li, Jiangbing Pan, Chao Chen

Secrecy Optical Communication System Based on Dynamic Strong Dispersion Control

An entirely new solution for secrecy optical communication system based on dynamic strong dispersion control is proposed in this chapter. Firstly, the theoretical principle of dynamic strong dispersion control and the system structure, especially the composition of encryption part and decryption part, are presented. Secondly, the feasibility and performance of the secrecy system are verified by numerical analyzation in a 40-Gb/s simulation system. Finally, the huge applicative potential of this system in various fields is pointed out.

Ju Cai, Qiujian Bai

A DFS-Based Traffic Grooming Algorithm for Light-Trail Networks

In order to maximize the throughput when accommodating all the requests for light trail, the traffic grooming problem was addressed. Two types of depth first search (DFS)-based traffic grooming heuristics were proposed at the scenarios of static case and dynamic case, respectively. DFS algorithm was adopted to calculate all the paths available according to the physical topology, while sorting algorithm was used to make the requests order according to the maximum tolerant delay or node sequence number at different phases. Numerical examples showed that the proposed heuristics can enhance the network throughput as well as minimize the network resource, such as wavelengths, etc. The proposed traffic grooming algorithms suits for the current light-trail network with the node number less than 6.

Minglei Fu, Yiluan Zhuang, Bisheng Quan, Zichun Le

A Simple Method for Studying LED Phase–Frequency Characteristics

The nonlinearity of phase–frequency characteristics of light-emitting diodes (LEDs) may cause the transmission signal distortion in visible light communication (VLC) systems based on LED illumination systems. In this chapter a simple and quick method was proposed to obtain the LED phase–frequency characteristics, which is very helpful for reducing this distortion. First, the LED transfer function was deduced from the carrier and photon density rate equations and the practical LED equivalent circuit. Then, experiments were designed to measure the LED amplitude–frequency characteristics, and the measurement programs for data transmission and processing were edited by LabView. Data of the amplitude-frequency curve were then used to fit the deduced function for extracting relative parameters. With determined coefficients the complete expression of the LED phase–frequency characteristics can be conveniently obtained finally. This method can provide an effective way to study the transfer function of VLC systems.

Peng Chen, Zixuan Xu, Yang Cao, Xiaofeng Gu, Zhen Zhong, Lei He

Analog Circuits and Signal Conversion Circuits

Frontmatter

A Novel Signal Conditioning Circuit for Piezoresistive Pressure Sensor

A novel signal conditioning circuit for piezoresistive pressure sensor is introduced in this chapter. The applied pressure is measured by Wheatstone bridge which can reduce the bad influence of the temperature. The circuit structure consisting of two operational amplifiers and three D/A converters is used to solve the problems about small output and temperature effects on output of piezoresistive pressure sensor. All sensor parameters are fully programmable and on-chip stored using integrated memory. Due to its architecture, the proposed circuit is easy to fabricate and realize. Simulation result shows that the total system error can be reduced to less than 1.8 % in a temperature range of 0–85 °C by means of the signal conditioning circuit at a 5 V power supply.

Siying Li, Zhengyuan Zhang, Jie Tang, Dasheng Ding

A Low Leakage Power-Rail ESD Clamp Circuit with Adjustable Holding Voltage in Nanoscale Process

A new power-rail electrostatic discharge (ESD) clamp circuit with ultra low leakage current and adjustable holding voltage, composed of an NMOS ESD clamp device and a new ESD detection circuit, is proposed in this chapter. The new ESD detection circuit has been verified in a 65-nm CMOS process. Simulating results show that the novel circuit has a standby leakage current of only 20.85 nA, which is two-orders lower than that of the traditional design. Also, by modifying the number of diodes in the circuit, we can adjust the holding voltage of the proposed ESD clamp circuit conveniently to achieve better immunity against mistrigger and transient-induced latch-on events.

Xuelin Zhang, Yuan Wang, Guangyi Lu, Song Jia, Xing Zhang

Design of Hybrid Continuous-Time/Discrete-Time ΣΔ Modulator

By combining advantages of continuous-time and discrete-time ΣΔ modulators, a novel hybrid continuous-time/discrete-time ΣΔ modulator was proposed which employs 4-bit quantization by transforming the discrete-time ΣΔ modulator to the continuous-time/discrete-time modulator which uses the impulse-invariant transformation. This modulator has low unit-gain frequency requirement for the first operational amplifier, which helps to reduce the power consumption effectively, making it more suitable for broadband applications. Moreover, the modulator is robust to the excess loop delay and

RC

product variation. The system-level modeling and simulation of the modulator were performed by using Simulink. At an oversampling ratio of 32 and an input signal bandwidth of 1 MHz, the modulator exhibited an ideal peak signal to noise ratio of 92 dB and a resolution of 15 bits.

Qi Shen, Weiyin Wang, Xiaofeng Gu

Design of the Self-Tracking Filter Based on Frequency to Voltage Conversion

In order to make cutoff frequency of filter that can be changed automatically with the time-varying signal, this chapter presents a new self-tracking filter structure which is based on frequency to voltage conversion. Input signal is converted into voltage signal through the F/V circuit. The output voltage of F/V is used to control cutoff frequency of the filter which is constituted of analog multiplier MLT04, current feedback amplifier AD844, a few resistors and capacitors. The design principle is introduced in detail, the design formulas are derived, and the circuit of self-tracking one-order low-pass and high-pass filter are given. When the input signal’s frequency is in the range of 10–100 kHz, the simulated and measured results show the effectiveness of this new method. The cutoff frequency of the filter can be adjusted automatically by the voltage which is proportional to frequency of input signal. So it realizes the frequency self-tracking.

Xingping Ran, Shengqian Ma, Juanfang Liu, Weizhao Zhang

Property of Butterworth Type Low-Pass Filter Used in Lock-in Amplifier for Precise Capacitance Transducer

Based on the fact that Op Amps of Butterworth low-pass filter is non-ideal, the transfer function of VCVS type two-order Butterworth LPF based on non-ideal Amps is deduced theoretically. The influence of non-ideal characteristic on filter is studied, and the relationship between step response and control time of filter based on non-ideal Amps and periphery circuit parameters is analyzed and calculated. The effect of LPF with non-ideal Amps on real-time of tiltmeter is evaluated. The control time and cutoff frequency of LPF are tested by experiment and the results are basically in accord with the theoretical ones.

Yu Huang, Li-Hua Wu

Comparative Study of Delta-Sigma Modulators for the Fractional-N PLL in WBAN

A delta-sigma modulator (DSM)-based fractional-N frequency synthesizer is the key component of wireless transceiver in wireless body area network (WBAN) system. The noise suppression performance, integration, and power of the DSM are difficult to balance in implementation. In order to choose a proper DSM topology for WBAN applications, a comparative study of single-loop DSM and Multi-stAge noise SHaping (MASH) DSM are presented in this chapter. Simulation and experiment results show that the MASH DSM is more suitable for WBAN applications with higher integration, lower power, and unconditional stability. Implemented in a 90 nm CMOS process, the proposed MASH DSM occupies an area of 40.5 × 45 μm and its power consumption is only 34 μW.

Qiming Zeng, Hang Yu, Jiang Lai, Yan Li, Zhen Ji

Low Power and VLSI Design

Frontmatter

A Comparison Analysis of Single-Ended Bit-Line Leakage Reduction Techniques at 40 nm Node

To analyze the single-ended bit-line leakage of SRAM at 40 nm node, two commonly used circuit techniques for reducing single-ended bit-line leakage were compared in this chapter. The first technique is 10T SRAM cell with read-buffer, which inhibits the leakage path from bit-line to ground when word-line is disabled. The experimental results showed that 10T SRAM achieved 3× improvement in bit-line leakage reduction compared to conventional 8T SRAM, but up to 5 orders of magnitude degradation in

I

on

-to-

I

off

ratio and less resistant to process variation were obtained. The other technique is Buffer-Foot (Buf-Foot) SRAM, which employs an 8T bit-cell but mitigates bit-line leakage uses peripheral buffer-foot to control the feet of read-buffers, achieving remarkably bit-line leakage reduction. The experimental results showed that the Buf-Foot SRAM exhibited 10–100× improvement in terms of leakage reduction from 1.0 V down to 0.2 V, up to 5 orders of magnitude improvement in

I

on

-to-

I

off

ratio, and 17.8× improvement in sensing timing window compared to 8T SRAM, also better tolerance to PVT. So, Buf-Foot SRAM has been founded a more promising solution to reducing bit-line leakage in advanced process technology compared to 10T SRAM.

Liang Wen, Zhentao Li, Yong Li

A 0.5 V Divider-by-2 with Forward-Body Bias Technique for Wireless Sensor Networks

As the CMOS technology scaling into nanometer and the power supply voltage decrease, low-voltage circuit design becomes a challenge. A divider-by-2 with 0.5 V power supply implemented in TSMC 0.13 μm 1P8M CMOS process is designed to produce 2.4 ~ 2.5 GHz quad-signals for Wireless Sensor Networks (WSN). To reduce the threshold voltage of transistors, low-threshold (LT) NMOS transistor in Deep-N-Well (DNW) with Forward-Body Bias technique is used in the circuits. The design of layout with DNW and isolation of the bulk of the LT NMOS with the substrate are explained in this chapter. The post-simulated operating frequency range is 2.5 ~ 7 GHz and the power consumption is 0.9 mW at 5 GHz.

Lidan Wang, Zhiqun Li

Implementation of a Built-in Temperature Sensor Using 65 nm 1.2 V Complementary Metal Oxide Semiconductor

This chapter proposes a built-in temperature sensor designed, and implemented, in deep submicron technologies for online thermal testing and monitoring of the Very Large Scale Integrated (VLSI) circuits. The temperature sensor utilizes the temperature coefficient for the threshold voltage of a metal oxide semiconductor (MOS) transistor. To minimize the influence of the operating point of an MOS transistor, it exploits “diode-connected” devices and very small aspect ratio device to detect the temperature variation. The sensor also delivers an extremely concise digital signal output based on a voltage-controlled relaxation oscillator. The simulation results show that the predicted temperature variation of the sensor is within 1 °C between −7 and +125 °C. The power dissipation is about 180 μW. And the number of the transistors needed is quite small. This sensor covering a small area of 135.8 × 65.15 μm

2

has been implemented in 65 nm complementary metal oxide semiconductor (CMOS) process. The function of the sensor has been proved functioning well between +30 and +100 °C with a 1.2 V supply voltage.

Xiao Wang, Bin Tian, Biao Wang

Design of Driving Platform for Ultra-High Resolution CCD

A design of driving platform for ultra-high resolution CCD imaging system which uses a Kodak-made full frame 50 M pixels CCD KAF50100 is proposed in this chapter. Inner structure and driving timing of the KAF50100 sensor are presented. Field Programmable Gate Array (FPGA) is used as the main device to accomplish the timing generation and control of the system. Design of the horizontal and vertical power driving circuits is presented. By using the Correlated Double Sampling (CDS) technique, the video noise is reduced and the SNR of the system is increased. A 12-bit A/D converter is used to improve the image quality. Experiment shows that top output speed of CCD sensor KAF50100 is achieved, pixel output rate is 4 × 18 MHz, maximum frame rate is 1fps, output noise is 2.76@12bit, and dynamic range is 63.4 dB. With better flexibility and extendibility, this design method can be widely used in ultra-high resolution imaging field like visible light underwater detection, satellite remote sensing and astronomical observation.

Wen-hai Xu, Hou-de Wu

IC Circuit Design and Test

Frontmatter

The Design of Pseudo-random Signal Transmitting Electromagnetic Detection System Based on FPGA

In order to overcome the shortcomings of the single transmission frequency and poor anti-interference ability of traditional geological exploration systems, this article designs a pseudo-random signal transmitting electromagnetic launch system based on the highly integrated, convenient, and flexible design characteristics of field programmable gate array (FPGA). Using linear feedback shift register (LFSR) and technology of direct digital frequency synthesis (DDS), the output signal has a random frequency, and it can effectively avoid the influence of the outside electromagnetic interferences which are difficult to remove in the past, and can increase the noise ratio in a low power to get satisfactory results. At the same time, it can transmit signals of multiple different frequencies in one power supply to improve the detection efficiency. It’s suitable for the exploration and development of our multi-mountain mineral.

Shiqiang Li, Guoqiang Liu, Yanhong Li, Zhengwu Xia

The Design and Application of Evolvable Hardware IP Core

This chapter designs an evolvable hardware IP (intellectual property) core for system call in order to solve problems of lacking flexibility in hardware system and difficulties in expending the general scale. The VRC IP core is realized by the description of bottom functions of VRC in VHDL and the organization of functional elements with SCH file. The core is characterized with reuse like the traditional IP core. However, compared with the traditional FPGA core, the interior circuit of the core may be evolved dynamically. Besides, the core may be used by any FPGA since it is designed in VHDL. Finally, the IP core evolves a motor control system in Spartan-3E FPGA and the evolved IP core is transplanted into a Virtex5 FPGA with high property. The experimental results show that the IP is provided with good portability and flexible connectivity.

Chuantao Li, Jianan Lou, Jianhua Yu, Fangfang Xie, Ruo Wendang, Miao Li

Design of a PWM/LDO Dual Mode Synchronous Buck Regulator

In order to improve some performance of the system under light load conditions, a PWM/LDO dual-mode system controlled by an external synchronous signal is presented here. In the work, we’ve designed a switching circuit based on the detailed analysis of the systematic structure and functions. The whole circuit was verified with Cadence simulations under the CSMC 0.5 μm CMOS process. The results show that when the input voltage

V

in

is 3.5–6 V, the output voltage

V

O

would be kept at 3.3 V and the operating frequency is about 1.2 MHz. In addition, the ripple of output voltage is less than 30 mV in PWM mode, while the ripple voltage is less than 10 μV and the maximum load current is up to 50 mA in LDO mode, and the converter’s overall efficiency is more than 80 %. Finally the whole circuit’s layout and post-simulation results are given. Consequently, this method can improve the overall efficiency of the system evidently.

Chang-yuan Chang, Qing Wang, Shuo-rui Zheng, Jun Li

Frequency Behavior of the Microcontroller Immunity Against the Conducted Radio Frequency Disturbance on Supply Pins

To understand the frequency response of the immunity of complex integrated circuits and to classify the immunity over a wide frequency range, this chapter developed a set of critical features for the immunity. A circuit model of the propagation network of the microcontroller system was established to simulate the immunity of microcontrollers against sinusoidal disturbance ranging from kHz to GHz on the supply pins. Critical features were defined according to the geometry of the simulated immunity curve. The origins of those features were investigated by checking the relationship between the feature positions and circuit components. The existence of those critical features was confirmed with immunity measurements. The defined set of critical features gives a valuable approach to characterize the immunity of complex integrated circuits over a wider frequency range.

Zixin Wang, Yehua Yang, Tao Su

A Novel Multi-RC-Triggered Power Clamp Circuit for On-Chip ESD Protection

In order to promote the electrostatic discharge (ESD) protection robustness of power clamp circuits, a circuit structure which has different turn-on and turn-off paths towards clamp transistor is used in our proposed novel multi-RC-triggered power clamp circuit. The proposed circuit uses CR structure as the ESD pulse detection component. Meanwhile, it also employs a nontraditional phase inverter in the turn-on path of clamp transistor. Simulation results show that the proposed circuit has long enough turn-on time of clamp transistor. And the ability of the proposed circuit to discharge static charges during an ESD event is notably enhanced through simulation. The clamp transistor would be automatically turned off after the fixed time delay in the turn-off path even if it is falsely triggered. The proposed circuit has simpler circuit structure while maintaining long enough turn-on time of clamp transistor, thus providing higher ESD protection robustness.

Guangyi Lu, Yuan Wang, Xuelin Zhang, Song Jia, Xing Zhang

Design of Trigger Circuit for Series SCR 12-Pulse Phase-Controlled Rectifier

According to the design requirement of series SCR 12-pulse digital trigger circuit, the key issues about the occurrence and capture of synchronization moment, the generation and phase-shift of firing pulses, and the amplification and isolation of firing pulses are elaborated in detail. The SCR digital trigger circuit using TMS320F2808 of TI Company is designed and verified with 25 kW experimental platform. Experimental results indicate that the trigger circuit meets the design requirement, and it has the advantages of steep leading edge of pulse, high trigger precision, accurate synchronization, modifiable trigger pulse, etc.

Yaming Ge, Jun Li

The Design and Implementation of Interface Electronics for Silicon Micromechanical Gyroscopes

This chapter reports the design and implementation of interface electronics for the silicon micromechanical gyroscope with electrostatic excitation and capacitive detection. In the proposed electronics, the charge amplifier is used for the capacitance readout, and the phase feedback loop and the direct-current feedback loop are applied to drive the drive axis at resonance with constant vibration amplitude. To obtain the input angular rate, the demodulator based on the phase-locked-amplifier is utilized. The electronics system comprises few analog parts (capacitance readout circuits) and the digital part based on FPGA is implemented and its performance is tested. The results show that the scale factor is 13.4 mV/(°/s) with a 46 ppm nonlinearity in the measurement range of ±150°/s and the noise floor is 0.002°/s/√Hz.

An-cheng Wang, Bing Luo, Xiao-ping Hu

Control Theory and Applications

Frontmatter

Design of Mamdani Cascade Fuzzy Control System for Inverted Pendulum

An inverted pendulum is a typically unstable and nonlinear system with multivariables and strong coupling. Fuzzy control theory is introduced to study pendulum swing angle stability problem and trolley displacement control problem. This chapter proposes Mamdani type of cascade fuzzy control design in which Mamdani fuzzy controller is used on the inner loop to control pendulum swing angle while Mamdani fuzzy controller is used on the outer loop to control trolley position. Simulink simulation results show that the fuzzy control design is highly efficient.

Zhaohong Ding

Intelligent Control Algorithm of Electric-Fused Magnesia Furnace Based on Neural Network

In order to solve the problems in electric-fused magnesia production such as large overshoot, electrode lift frequency and arc current instability that are caused by two-point control algorithm and three-phase electrode control, respectively, this chapter designs an integrated three-phase control model of electric-fused magnesia furnace which is based on improved BP neural network which trains the neural network control model by using the sample data got from production floor and establishes the neural network controller model through the weights of training results. Through research and simulation analysis, feasibility and availability of the control method are proved. This control model can solve the problem of large overshoot in traditional manufacturing method, and then reduce production energy consumption and improve the quality of products.

Wenlai Ma, Shouxi Zhu

Dynamics and Control of an Active Magnetic Bearing-Rotor System with Time Delay

Time delay in digital control loop, which is usually neglected in most of the research in electromechanical systems, may have great influence on the performance of high-speed active magnetic bearing (AMB) systems. In order to study time delay’s effect on system stability and dynamics, a 2-degree rigid rotor-magnetic bearing system was employed and the stability boundary of time delay on this system was discussed. Then a control law of compensation for time delay was presented and a state predictive module was introduced into closed-loop control system. Simulation results showed the control performance degraded owing to computing time delay, and the system became unstable when time delay exceeded the upper boundary. Then via the addition of time delay compensating module, the control performance is well improved. It is clearly indicated that it is necessary to take time delay into consideration when the dynamics and control problem of high-speed AMB system is studied. The control strategy presented in this paper can compensate the negative effect of delay effectively.

Mingshu Zhang

Multimodel Nonlinear Predictive Control with Gaussian Process Model

In industrial practice, parameters of plants are often not fixed in production process. The variation of parameters gives rise to the variation of system model. With model-based predictive control, the plants will be out of control if a fixed predictive model is applied when the parameters of plants change frequently. This paper proposed a multimodel nonlinear predictive control based on Gaussian process models which can be applied to the nonlinear system control with varying parameters. On the basis of the management ability of Gaussian process in fitting nonlinear model, a feasible switch strategy based on deviation of the predictive output from the actual output was applied to identify change of parameters. A two order dynamical system with four models switch was demonstrated to illustrate this algorithm. According to simulation results, this switch strategy can identify the change of system model accurately and quickly.

Ming Hu, Zonghai Sun

Availability Analysis of a Redundant System with Common-Cause Failure

In order to analyze the availability of a redundant system with common-cause failure (CCF), a developed availability model was proposed in this article, which assumed that several components or the whole system would fail to perform its function if a CCF occurs. Markov method was used to describe the model. And this article probed into the calculation method on availability index and obtained its numerical solutions. For illustration, an electric sources example which is a 2/3(

G

) system actually was utilized to show the effect of redundancy and CCF. The results showed that the availability of redundant system was higher than that of the system without any redundancy. Moreover, availability of redundant system without CCF worked better compared with that with CCF. Availability modeling by Markov method for redundant system with CCF was more convincible than that without CCF. And it showed that CCF had non-negligible adverse influence on availability.

Yansong Liang, Xianhui Yang, Jun Wang

Measurement, Tracking, and Space Technology

Frontmatter

Study on LQG Regulation Design of DC Motor

Designing a Linear-Quadratic-Gaussian (LQG) regulator is the most convenient, reliable, and economical way to optimally dynamic control the target object. LQG uses Kalman filter to observe the state of the system, especially for specific system noise and system measurement noise. The system model of LQG regulator is a linear system using the state-space form, and its objective function is a quadratic function of the state and the input. It uses Kalman filter to observe and track system state. By changing LQ-optimal gain

K

continuously and minimizing the quadratic cost function, it realizes the optimal dynamic control of the target object. It can be observed from MATLAB simulation that the unit step response curve of the closed-loop system with LQG controller monotonic decays immediately after slightly overshooting. It reflects that optimal performance has been achieved in this kind of design.

Guoliang Liu, Haitao Gao

Scalar Magnetometer Configuration Scheme for Underwater Magnetic Anomaly Localization

Aiming at the problem that it is necessary to measure precisely magnetic gradient tensor in underwater localization method based on geomagnetic anomaly inversion, the feasibility of scalar magnetometer configuration scheme for magnetic gradient tensor is discussed. The measurement equation of magnetic component gradient in scalar magnetometer configuration scheme is deduced theoretically, and it proves that magnetic gradient tensor can’t be measured by scalar magnetometers even more. The calculated error of magnetic magnitude gradient is analyzed, and the statistic law of gradient measurement error is inferred on condition of Gauss magnetic measurement noise. According to these, the selection principle of gradient measurement baseline length is pointed out.

Li-Hua Wu, Yu Huang

Attitude Disturbance and Control of Satellite During Space Net Projecting

The space net is a novel and effective approach in solving the spacecraft capturing problem. In this chapter, the attitude control problem of parent satellite is addressed. At first, the disturbance imposed on the parent satellite is analyzed, and the dynamic process of mass ejection is investigated. In addition, the main factors that affect the performance of the net are analyzed, and based on which, the model of the disturbance torque is developed. At the end of this chapter, the numerical simulations are implemented, and the corresponding results validate the effectiveness of the proposed algorithm.

Zhijie Gao, Dongfang Yang, Fuchun Sun

Optimal Sliding Mode Attitude Synchronization Control for Autonomous Docking to an Out-of-Control Target

In order to solve the attitude synchronization control problem for an on-orbit servicing spacecraft autonomous docking to an out-of-control target in the presence of unknown bounded disturbances, system uncertainties and measurement noise, an optimal sliding mode control law is presented in this paper. By using the optimal control method, the first sliding surface was obtained, which is an optimal sliding surface. Then, the second sliding surface was obtained by the integrating the signum function of the first sliding surface, which was used to autonomously compensate the disturbances and model uncertainties. Furthermore, an optimal sliding mode control law was designed by the sliding mode control method. The relative attitude variables will converge to the origin in the sense of optimality with a predetermined quadratic cost function after the system reaching the first sliding surface. Simulation results verified the effectiveness of the designed optimal sliding mode control law, and the robustness to the unknown bounded disturbances, system uncertainties and measurement noise were also demonstrated.

Yunhai Geng, Wei Lu, Ling Yi, Xiaowei Shan

Precession-Identification Based on Sparse Representation

The precession-identification, on the background of ballistic missile defense, is studied. Based on sparse representation, a detecting procedure and a corresponding parameter estimation principle are proposed in this paper. The method can judge the existence of precession-modulated signals and estimate the precession parameters. The experimental results demonstrate the effectiveness of the method. The precession-identification method would be useful for the practical application.

Yi Xu, Peng You, Hongqiang Wang

Identification of Thermal Process Using Hammerstein Model Based on Particle Swarm Optimization Algorithm

In order to identify the controlled objects which are nonlinear time-delay processes with slow time-varying in the thermal system accurately, the Hammerstein model and particle swarm optimization (PSO) algorithm were used in this paper. For the Hammerstein model discussed in this paper, the polynomial and difference equations were used to express the nonlinear part and linear part of Hammerstein model, respectively. This study used the PSO algorithm to find the optimal solution of Hammerstein model’s undetermined parameters in the parameters space. For illustration, an example of main-steam temperature system identification was utilized to show the feasibility of the Hammerstein model based on PSO algorithm in identifying the thermal system processes. The PSO-based Hammerstein model can effectively represent the controlled objects which are nonlinear time-delay processes in the thermal system and thus a class of identification problems with nonlinearity in thermal system can be solved.

Dong Feng Wang, Yan Yan Ren, Chang Liang Liu, Pu Han

Robotics, Automation, and System Identification

Frontmatter

Fuzzy PID Control of Six Degrees of Freedom Parallel Manipulators in Electro Hydraulic Servo System

In order to solve the problems with the 6-DOF parallel robot controlled by traditional PID controller, such as slow response, low control accuracy, and poor robustness, this chapter designs a fuzzy PID controller via fuzzy-adaptive PID control algorithm. The fuzzy control rules are designed through the establishment of a membership function based on given language variables. At last, Matlab is employed to simulate the PID controller and the response of ordinary PID controller to the open-loop transfer function. Experiments show that the designed fuzzy PID controller, with the features of fast response, strengthened robustness, high accuracy, and no overshoot, enhances the performance of control of 6-DOF parallel robot.

Danhong Sang, Chenghao Han

Jointly Connected Topologies and Its Application to Cooperative Timing Mission of Multiple Unmanned Air Vehicles

For the average consensus of multi-agent systems, the LMI-based delay-dependent stability criterion is provided with jointly connected topologies. Using the idea of state decomposition, the condition for guaranteeing average consensus is converted into verifying the stability of zero equilibrium of disagreement system. Considering multiple time-varying communication delays, common Lyapunov–Krasovskii functional is employed to analyze the stability of zero equilibrium. In order to relax the conservativeness, Free-weighting Matrices method is employed in the main results. After matrix order-reduced treatment, the tolerant upper bounds on communication delays can be obtained through solving feasible linear matrix inequalities (LMIs). Numerical results are given to demonstrate the benefit on reducing conservativeness of the proposed method. At last, we apply distributed average consensus algorithm to cooperative timing mission of multiple unmanned air vehicles (UAVs) under limited communication conditions.

Man Li, Qing jie Zhang, Guang dong Liang, Zhi ke Wang

Normalized Two Inputs Single Output Hammerstein System and Its Application

In order to improve the description ability of Hammerstein system, the two inputs single output (TISO) Hammerstein system and normalized TISO (NTS) Hammerstein system are introduced and their mathematical representation are firstly presented. Through two input ports, the model can describe the nonlinearity influence of the two inputs to system output and normalizing two input variables can solve the parameters switching problem. The addressed models are applied in the nonlinear identification of supercharged boiler combustion system. The results show that the TISO nonlinear Hammerstein system can reflect the nonlinear influence of the two inputs to system output effectively and ideal identification accuracy can be obtained with only one set of parameters based on NTS Hammerstein system. So, the TISO Hammerstein system and NTS Hammerstein system improve the description of Hammerstein system greatly.

Jia-feng Zhao, Xiu-zhen Ma, An-ming Rong

An Improved Calibration Method of Micro Stereo Vision System

To improve calibration accuracy of micro stereo vision system, this chapter analyzes the calibration method based on least-square regression and parameters calibrated by weak disparity micro stereo vision model. The problem that system parameters are sensitive to noise is discovered. It can result in instable accuracy of the system. Therefore, the minimum uncertainty constraint is introduced in the calibration of the rectification parameters. It fine-tunes the magnification to realize that the two half angles and focal length in the two subsystems of stereo light microscope approximately equal each other, while the combined uncertainty is minimum. Experimental results demonstrate that the proposed calibration method is robust and effective in micro stereo vision system.

Wei Pei, Yong Ying Zhu

Knowledge and Learning Technologies

Frontmatter

Alarm Association Rules Mining in Distributed Database

In order to conduct more conveniently the alarm correlation analysis in distributed databases recently, this chapter presented a novel algorithm FPT-DM for distributed association rules mining. FPT-DM uses FP-tree structure to generate local large itemsets and exchanges messages between two sites in the network, for this method has low time complexity and communication overload. Experiment results showed that FPT-DM was feasible and efficient. Compared with classical distributed algorithms, FPT-DM can improve 40 % efficiency.

Chao Chen, Tongyan Li

An Improved Ant Colony Algorithm for Solving Permutation Flow Shop Scheduling Problem

To solve permutation flow shop scheduling problem, a scheduling algorithm based on ant colony optimization is proposed in this chapter. This algorithm is an improved ant colony algorithm. On the basis of self-adaptation ant colony optimization algorithm, the variation method of adjust operation and noise interference method are used to improve the algorithm. Finally, the improved ant colony algorithm and the traditional genetic algorithm are compared by the simulation results. Besides, the advantages of the improved ant colony algorithm are also analyzed. The permutation flow shop scheduling problem can be well solved by this improved ant colony algorithm.

Zhi Cai, Zhijun Gao, Xuejin Zhang, Weilai Hao

Nonlinear Data Mining Method Based on Manifold Learning

A new nonlinear data mining thought based on manifold learning was proposed to solve the difficult problem of nonlinear data processing. Three manifold learning methods, that are Isometric Mapping (Isomap), Locally Linear Embedding (LLE), and Diffusion Map (DM), were used for nonlinear data mining and then the results were expressed by visualization. The availability and validity of the methods were verified by data.

Lurui Xia, Jilian Li, Xiaoping Du, Gangtao Hao

Improved Convex Incremental Extreme Learning Machine Based on Enhanced Random Search

In order to further improve the performance of the existing incremental extreme learning machines (I-ELMs), this chapter proposes an improved convex incremental extreme learning machine based on enhanced random search (ECI-ELM). In ECI-ELM, an enhanced random search method is incorporated into ELM where a convex incremental method is used to add hidden nodes. It is proved that such ECI-ELM can still approximate any continuous target function for the widespread-type piecewise continuous hidden nodes. Simulation results show that ECI-ELM can produce better generalization performance at a faster convergence speed and obtain more compact network architecture than convex incremental extreme learning machine (CI-ELM) and enhances the incremental extreme learning machine (EI-ELM).

Wei Wang, Rui Zhang

C-PESA: An Improved Comentropy-Based PESA Algorithm

To solve the increasing complexity with the growth of solution sets number in PESA, we present a comentropy-based PESA algorithm (C-PESA), which is an evolutionary algorithm of multi-objective optimization. In C-PESA, the gradual development and maturity of the solution sets can be observed with the continuous calculation of entropy values. This determines whether to stop the optimization process, and accordingly simplifies the run-time complexity of the algorithm to a certain degree. Simulation results show that the calculation amount of C-PESA increases linearly with the increasing number of population, and the efficiency of evolutionary algorithm also improves.

Kun Wang, Linlin Wang, Yuhua Zhang

Study of the Hydrological Time Series Similarity Search Based on Daubechies Wavelet Transform

Analysis of series similarity plays an important role in hydrological series data mining. Mallat algorithm and Daubechies wavelet can be applied to discrete transform hydrological series. After running k layers discrete wavelet transform, hydrological series can be broken down into approximate part

A

and detail part

D

with different time scales, and the length of

k

layer series is only 1/2

k

of original series’ length. Then similarity search can be performed on transformed series, and this search costs less than original similarity search.

Hongfa Wang, Chen Xing, Feng Yu

Bidirectional Search Algorithm of Available Logistics Route Based on Site Closure

To overcome the shortcomings of medium and small logistics companies, such as narrow coverage of transport network and service with single form, a way of setting up the logistics alliance was proposed. For the problem of choosing the transshipment company and logistics route in cooperative transportation, the bidirectional search algorithm of available logistics route based on site closure is designed and realized. The concept of site closure is introduced to compute all directly reachable sites. Both on origin site and destination site, the closure operation is made one by one to obtain available routes. The experimental result indicates that transshipment company routes and site routes are in conformity with reality by this algorithm, which not only enhances the search efficiency of logistics routes but also can obtain available logistics routes and has better practical application value.

Min Song, Xiaoling Su, Chong Zhang

Pattern Recognition and Machine Intelligence

Frontmatter

Geological Deformation Trends Based on Dynamic Fuzzy Neural Networks

In order to analyze the complex and chaotic geological deformation data better, a model of Dynamic Fuzzy Neural Networks is used in this chapter. The latest geological deformation data from high-precision GPS monitoring system is selected as training and prediction sample. Dynamic Fuzzy Neural Networks may grasp most characteristics information of the original data through studying and training the sample. At the same time, we will summarize the singularity of the data. Empirical results show that the model of Dynamic Fuzzy Neural Networks can be used in analyzing the geological deformation data and predicting its short-term trends. Furthermore, it provides a new solution to explore the geological deformation data trends and make relevant short-term prediction.

Zhifei Yang, Lin Zhu, Jianhui Yang

Face Recognition Based on a 2D Gabor-Modular Binaryzation-LDA Feature Extraction Method

In this chapter, a novel feature extraction method (Gabor-modular binaryzation linear discriminant analysis (GMBLDA)) for face recognition is presented. 2D Gabor wavelet feature extraction is more robust for illumination and facial expression, however, the dimension of Gabor wavelet is very high and the redundancy rate becomes larger when it is used to feature extracting. For heavy work calculating, the poor real-time, and some other problems, this chapter proposes a way of integrating 2D Gabor-LDA with blocking and binaryzation. Transform face images to 2D Gabor wavelet at first and then use the blocking and binaryzation to reduce the dimensions and finally use LDA transformation to obtain the optimal classification characteristics. Experiment results based on YALE face database demonstrate that this method can achieve a higher recognition rate and a better recognition effect compared with the traditional way such as Gabor, principal component analysis (PCA), LDA, and Gabor + LDA (GLDA).

Wenbiao Jiang, Mei Xie

Fuzzy Clustering with Generalized Entropy Based on Neural Network

In order to solve the optimization problem with generalized entropy’s objective function, where weight index and the generalized entropy coefficient may be equal or not equal to each other, the multi-synapses neural network is used in this chapter. For the constraints of the objective function, we use augmented Lagrange multipliers instead of Lagrange multipliers to construct augmented Lagrange function. On the basis of multi-synapses neural network, we obtain a generalized entropy fuzzy

c

-means (FCM) algorithm, namely GEFCM. Moreover, to solve Lagrange multipliers’ assignment problem, we use randomly selected method and iterated method to determine them. Experimental results show that for the different weight index and generalized entropy coefficient in data clustering, algorithm’s performance has a very large difference. Especially, when weight index is greater than 2, good clustering results are also obtained with presented algorithm GEFCM.

Kai Li, Peng Li

New Recursive Robust Algorithms for the Estimation of AR Parameters

In order to overcome the difficulty that general robust algorithms are not robust when they are applied to the estimation of autoregressive (AR) parameters in the presence of additive outliers, a new recursive robust estimator for regression and its improved version are proposed in this chapter. The estimator is derived by solving the “normal equation” of the employed cost function using one-step iteration method recursively. The new version is extended from the estimator by modifying the original model conditionally. The simulation results show that the estimator gives a slightly high accuracy than other related estimators while the latter can perform well in nonstationary environments. It is concluded that both of them can suppress the adverse effect of outliers and the latter is more suitable for the estimation of AR parameters.

Junmin Zhang, Yuanli Cai

Application Research of Support Vector Machine Classification Algorithm

In order to improve classification capability, an advanced support vector machine (SVM) algorithm (L2-SVM) was studied in this chapter. Theoretical analysis of L1-SVM and L2-SVM illuminated the solving process of classification problem by using these two algorithms. The analysis also indicated that middle-scale datasets can be correctly classified by SVM algorithm. Both algorithms can be realized with the help of MATLAB. Simulation was conducted by using two spirals datasets. The results showed that both L1-SVM and L2-SVM had very good classification capability. The identification rates of these two algorithms were better than those of neural network algorithm and nearest neighbor algorithm. In some conditions, L1-SVM and L2-SVM were consistent. Compared with L1-SVM, L2-SVM had larger model parameter adaptable space. L2-SVM was proved to be an excellent algorithm for optimal parameter searching and classification both theoretically and experimentally, which will play an important role in recognition field.

Weiguo Dai, Haitao Li, Qijun Liu

Improved Clustering Algorithms Used in Diesel Engine Vibration Fault Diagnosis Based on Bayesian Networks

The work presented in this chapter focuses on diesel engine vibration fault diagnosis. The vibration fault of diesel engine has the property of randomness and layers, and its fault information has the features of uncertainty and non-integrality. The chapter studied the method of typical diesel engine vibration fault diagnosis based on Bayesian networks (BNs), which used expert knowledge to determine conditional probability, converted fault information into numeric data, and then established the Bayesian network model. The clustering algorithms were improved to reduce calculation work and enhance the accuracy in the diagnosis by way of optimizing correlation value between Bayesian network nodes. Simulation and experimental results verified the effectiveness of the improved clustering algorithms.

Zhaojing Tong, Xinliang Zhang, Aihua Dong, Xiuhua Shi, Jingjing Du

An Algorithm of Moving Objects Localization Based on Neighboring Analysis

Accurate detection and location of moving objects is fundamental in surveillance application systems. Clustering methods are often applied to find the objects. However, this type of method is often confronted with some impediments, such as spoiled regions’ connectivity, a lot of outliers, great disparity between moving object regions, etc. In order to solve these problems, the chapter proposes a locating algorithm of moving objects based on neighboring analysis. Firstly, the neighboring relationship is analyzed between foreground pixels which are sampled from the background subtraction’s results, and a neighboring feature matrix is extracted. According to it, the initial clustering is obtained by linking the nearest samples. Furthermore, to minimize the criterion function, some clusters merged according to the relationship of the intra-class link function and the inter-class link function. Thus, all the samples converged into a conclusive number of clusters. The experiments indoors and outdoors demonstrate that it works effectively. The computational complexity is found to be proportional to the number of foreground moving objects.

Jiasheng Song, Guoqing Hu

The Recognition of Leaf Shapes Based on the Analytic Hierarchy Process

Aiming at the plant automatic classification in the precision agriculture, the leaf shape recognition method based on the characteristics of the plant geometric figure was proposed. Several geometric parameters, such as the aspect ratio, lobe number, and invariant moments, were extracted as the features for leaves classification. The analytic hierarchy process was employed to identify leaf shapes. In the first layer of classification, the types of leaf shapes were determined by comparing threshold and the aspect ratio. In the second layer of classification, the broad leaf was classified into single-lobed leaf or multiple-lobed leaf according to lobe number. In the third layer of classification, the minimum distance decision rule was used to identify single-lobed leaf shapes according to their invariant moments. The experiments showed that the analytic hierarchy process can identify leaf shapes effectively and the results of classification were consistent with the human judgment. The leaf shape recognition method has laid the foundation for automatic plant classification.

Bo Liu, Chenxiang Lin, Qiu Fan

Dimensional Reduction Applied in Lung Data’s Classification

To improve the classification accuracy for the gene expression data, several methods (Laplacian Eigenmaps and PCA (principle component analysis)) were used to reduce the original data’s high dimension. Raw data was computed in nonlinear or linear algorithms, and classified by SVM (support vector machine). In the experiments, the classification accuracy was significantly improved after dimensional reduction. The dimensional reduction strategy can effectively improve the accuracy of classifying gene expression data.

Fei Yin, Guirong Weng

Modeling, Simulation, and Data Processing

Frontmatter

Environment Factor Simulation in Double Parameters Weibull Distributing

In order to solve the problem of the low precision in environment factor evaluation and difficulties in physical modeling, a method based on Pspice simulation for environment factor evaluation is proposed in this chapter. Through the transient analysis, Monte-Carlo analysis, and temperature analysis in Pspice, the performance simulation data can be used to solve this problem with the accelerated performance test theory. For illustration, an example is utilized to show the validity and feasibility of the Pspice simulation in solving the environment factor evaluation problem. The results show that this method is an effective way in environment factor evaluation. The method based on Pspice simulation avoids the difficulties in physical modeling and has sufficient precision. With the environment factor, the data from various stresses can be converted to one single stress in order to evaluate the reliability.

Meng Lv, Jinyan Cai

Researches on Control of Iterated Function System Attractors

In order to enhance the ability of iterated function systems (IFSs) expression of nature things, this chapter introduces some simple methods to control the local structure of IFS attractors and the color of their images. Different from the former methods, the new method can control interrelation between the whole entity and the parts, and the interrelation between different parts by mapping control strings and matrixes. Finally, the effects of the method are shown by computer experiments in the simulation of trees.

Xiangdong Liu, Zhanguo Li, Degao Wang, Liming Wang

Organization of LiDAR Point Cloud Based on 2D

Having pointed out the one-to-one mapping between LiDAR ground point cloud and its projection on horizontal surface, through analysis of common methods of point cloud data organization, an advanced 2D data organization based on regular grid and quadtree is put forward. Firstly, this chapter divides the point cloud by Cartesian coordinates and creates grid spatial index with Hash table. Then it creates quadtree in each cell. It has solved the inefficient problem when massive points are stored in one quadtree. Furthermore, it can be used in uneven discrete point cloud. Experiment proves that the method greatly improves the efficiency of data organization and data index.

Hengguang Bi, Zhigang Ao, Youoliang Zhang, Kangyi Zhang, Changchun Tang

Denoising Method for Gross Errors and Random Errors of Monitoring Displacement for High Rock Slope

Data denoising is an important issue for data processing. The gross errors in a nonlinear time series are detected by using the three-standard-deviation rule (3-σ rule) and by reconstructing the time series by a first-order Lagrange interpolation method. Then the reconstructed time series is used to denoise the random errors by a discrete stationary wavelet transform (DSWT) method. Finally, the present data denoising method is applied to the error analysis of the slope displacement monitoring data collected at the Jinping I Hydropower Station. Computed results show that the data denoising results can be improved through removal of the gross errors and repair of the time series followed by application of wavelet transforms to denoise the random errors.

Wei Hu, Xingguo Yang, Jiawen Zhou, Lin Zhang, Hongtao Li

Assessment of Storage Reliability for Accelerometer Based on Pseudo-Stable Data

Because of the slow parameter drifting and the long testing time in storage environment, the life test has failed to meet the actual needs in normal environment, so it is difficult to assess the reliability of the product accurately. The power function degradation model and the Arrhenius acceleration model are introduced in the paper based on the degradation mechanism of accelerometer parameters, and a generalized analysis method of high reliable and long life is also proposed under the pseudo-stable condition obeying the log-normal distribution and the Weibull distribution. The experiments proved that the proposed method can overcome the disadvantage in reliability assessment for traditional accelerated data, eliminate the defect of the accelerometer reliability interval evaluation, and improve the accuracy and stability of the reliability index, so it has higher cost-effectiveness ratio.

Dongyao Jia, Yanke Ai

Virtual Prototype Design Technique of the CJ20-100 Model Alternating Current Contactor

Virtual prototype of the CJ20-100 model up-and-down AC contactor is accurately created by combining function of creating rigid body models on ADAMS with function of creating flexible body models on ANSYS. Electromagnetic attraction which is measured in test is imported into ADAMS simulation environment. Accuracy of virtual prototype is verified by comparing it with displacement curve of iron core in real test. Finally, optimal design of spring’s coefficient is done with virtual prototype of AC contactor. In addition, virtual prototype of CJ20-100 type up-and-down AC contactor can be used to optimize other AC contactor’s design parameters for improving overall performance of AC contactor.

Dewei Chen, Yuqi Zhuang, Yangxing Xie, Yuanpeng Huang

Software, System, and Network Security

Frontmatter

An Approach to Verify Correctness of the Mandatory Access Control Framework

Mandatory access control (MAC) refers to a type of access control by allowing administrators to enforce constraints on user and application behavior. Xen Hypervisor is an open source virtualization platform that allows multiple computer operating systems to execute on the same computer hardware concurrently. The Xen Security Module (XSM) is a MAC system being built into Xen, similar to the Linux Security Modules (LSM)/SELinux for Linux. According to the property of XSM, we introduce the selective symbolic execution method and implement a correctness verifying testing tool. This tool can verify the accuracy and completeness of the hook functions in Xen Security Module.

Xiaokun Zhang, Ri Xu, Yan Zhang, Geng Zhao

Extending Explicit Management of SMMHS to OpenMP for Heterogeneous Architectures

In heterogeneous architectures with software-managed memory hierarchies system (SMMHS), software is deployed in charge of data placement of device memories and data movement between main memory and device ones. Considering the simplicity, portability, and performance characteristics of OpenMP, we argue that it is the most appropriate model for high level heterogeneous system programming. In this chapter, we address the problem of managing data storage and data transfer within SMMHS by proposing a potential extension to OpenMP. Meanwhile, we develop a method to compute the array region by applying the polyhedral model. Finally, we implement the automatic generation of the extended OpenMP clauses based on Open64, providing support for the migration of sequential programs to heterogeneous platforms. The experimental results show that OpenMP programs automatically generated with extended clauses get significant performance improvements on heterogeneous architectures. The extended OpenMP clauses could improve data placement of device memories and data movement between main memory and device ones evidently.

Xiaoxian Liu, Rongcai Zhao, Yuan Yao, Pinfeng Huang

Equidistant Checkpoint Placement for Checkpointing and Rollback Recovery

To derive the proper equidistant checkpoint interval for log-based checkpointing and rollback recovery mechanism, a directed state transition model of the system execution is presented under the assumption that the inter-failure time follows the exponential distribution. Various related essential factors are considered synthetically in this model. Combined with Laplace transform, the fault-tolerant overhead ratio is derived by evaluating the expected total execution overhead of a single checkpoint interval. Finally, the optimal equidistant checkpoint interval can be obtained. The metrics show that the derived formula is more practical to determine the checkpoint placement for log-based fault-tolerant performance optimization and the degenerated formula agrees with the previous model.

Zhenpeng Xu, Weiwei Li, Jinyong Yin

SSE Instruction and Block Predetermination-Based Automaton Optimization

Techniques to decrease the memory requirements of large patterns set for an intrusion detection system (IDS), block predetermination, and block matching based on a self-balancing binary search tree (AVL) are defined in this chapter. By introducing SSE instruction, the new DFA matching system can increase matching efficiency when compared to the standard AC implementation. For illustration, a number of tests, according to different lengths or different amount of patterns were used to show how many DFA states and how much memory can be saved by the design. Empirical results show that at best an SSE-AVL-based implementation of DFA can save about 98 % of memory usage in common DFA when using randomly generated patterns. The hybrid of block DFA and common character DFA can effectively suppress memory requirements, and with the help of block predetermination with two-level-AVL filtration and SSE instruction, the matching speed performs better than standard AC under single process case.

Tianlong Yang, Hongli Zhang, Xiaolong Cao, Zhihong Tian, Mahmoud T. Qassrawi

A New Signature Scheme from Inner Automorphism Group

A signature scheme based on the discrete logarithm problem (DLP) over inner automorphism group is proposed and proved to be existentially unforgeable against adaptively chosen-message attack. The construction in this study can be viewed as a noncommunicative variant of Schnorr signature scheme. Performance-related issues are also addressed in detail. By comparison, the scheme is efficient in terms of running time and storage space.

Ping Pan, Chengqian Xu, Licheng Wang, Yixian Yang

New Multi-Receiver Id-Based Ring Signcryption Scheme

The first multi-receiver id-based ring signcryption (mIBRSC) scheme was proposed by Lal et al., which enables the user to anonymously deliver some important information to multiple receivers in a secure and authenticated manner. In this chapter, we show that their scheme is insecure against adaptive chosen ciphertext attacks. Furthermore, we present an improved mIBRSC scheme, which satisfies both confidentiality and unforgeability in the random oracle model.

Xing Wang, Jian Shu, Wei Zheng, Linlan Liu, Xin Fan

Image Scrambling Based on Linear Distortion

A novel image scrambling algorithm based on linear distortion is proposed in this chapter. The scrambling process is performed in frequency domain with a two-dimensional encryption key to change the amplitude and phase components of image signal, respectively. The analysis of the simulation shows the validity of the algorithm.

Shanshan Li, Jiang’an Wang, Bayi Qu

Backmatter

Additional information