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2010 | Buch

Life System Modeling and Intelligent Computing

International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, Wuxi, China, September 17-20, 2010. Proceedings, Part I

herausgegeben von: Kang Li, Xin Li, Shiwei Ma, George W. Irwin

Verlag: Springer Berlin Heidelberg

Buchreihe : Communications in Computer and Information Science

insite
SUCHEN

Über dieses Buch

The 2010 International Conference on Life System Modeling and Simulation (LSMS 2010) and the 2010 International Conference on Intelligent Computing for Susta- able Energy and Environment (ICSEE 2010) were formed to bring together resear- ers and practitioners in the fields of life system modeling/simulation and intelligent computing applied to worldwide sustainable energy and environmental applications. A life system is a broad concept, covering both micro and macro components ra- ing from cells, tissues and organs across to organisms and ecological niches. To c- prehend and predict the complex behavior of even a simple life system can be - tremely difficult using conventional approaches. To meet this challenge, a variety of new theories and methodologies have emerged in recent years on life system mod- ing and simulation. Along with improved understanding of the behavior of biological systems, novel intelligent computing paradigms and techniques have emerged to h- dle complicated real-world problems and applications. In particular, intelligent c- puting approaches have been valuable in the design and development of systems and facilities for achieving sustainable energy and a sustainable environment, the two most challenging issues currently facing humanity. The two LSMS 2010 and ICSEE 2010 conferences served as an important platform for synergizing these two research streams.

Inhaltsverzeichnis

Frontmatter

The First Section: Intelligent Modeling, Monitoring, and Control of Complex Nonlinear Systems

Research on Steam Generator Water Level Control System Based on Nuclear Power Plant Simulator

Steam generator (SG) is one of the most important equipments in nuclear power plants. The water level of SG must be kept in a certain range to ensure the plants operate safely, reliably and economically. Nowadays, most SG water levels are controlled by PID in PWR plants. In this paper, the mathematical models of SG level control system are built by Matlab/Simulink; the simulation research based on the Matlab/Simulink models is conducted, too. Then, based on RINSIM simulation platform of nuclear power plant Simulator in Wuhan University, a simulation model on the SG level control system is established.The graphical modeling methods for the SG level control system are provided. By using the model, transient simulation experiments and researches with different conditions are conducted. Contrast with the Matlab/Simulink simulation models, the good preciseness and identification performance of the RINSIM models are verified.

Jianghua Guo
Stabilization for Networked Control Systems with Packet Dropout Based on Average Dwell Time Method

This paper proposes a new stabilization method for network control systems with stochastic packet dropout and network-induced delays. In terms of stochastic packet dropout, the NCS is modeled as Bernoulli process with two modes. By using average dwell time method, the sufficient conditions of NCS and the state feedback controller are derived.

Jinxia Xie, Yang Song, Xiaomin Tu, Minrui Fei
Modeling of Real-Time Double Loops System in Predicting Sintering’s BTP

In this paper, a double loops system, which based on the property of the large delay and time-varying of sintering process, is proposed to solve a challenging problem for building a system model of dynamic vary structure and vary weights from the given input and output data to predict the burning through point (

BTP

). A position track fuzzy controller is used to adjust the speed of sinter in outer loop, and an optimum Self-organizing Genetic Algorithms Neural Networks is also presented. The comparison of the actual process and the simulative process by OSGANN demonstrate that the performance and capability of the proposed system are superior.

Wushan Cheng
An Orthogonal Curvature Fiber Bragg Grating Sensor Array for Shape Reconstruction

An orthogonal curvature fiber Bragg grating (FBG) sensor array is introduced, and it can detect the deformation and vibration of flexible structures such as rod, keel, etc. The sensor array composed of 20 sensors which were averagely distributed on four optical fibers was mounted on the body of cylindrical shape memory alloy(SMA) substrate with staggered orthogonal arrangement. By the method of calibration, the relation coefficient between curvature and wavelength shift was obtained and the curvature of sensor was calculated accordingly, then, the space shape was reconstructed with the help of the space curve fitting method based on curvature information of discrete points. In this paper, the operation principle, the design, packaging, calibration of FBG sensor array and the method of experiment were expounded in detail. The experiment result shows that the reconstructed spatial shape is lively, thus indicates that the relevant method and technology are feasible and practicable.

Jincong Yi, Xiaojin Zhu, Linyong Shen, Bing Sun, Lina Jiang
Implementation of the PCB Pattern Matching System to Detect Defects

FPGA-based PCB Pattern Matching System, which supports a Camera Link (Medium), was used to detect PCB defect patterns. For the automation of the vision inspection of the PCB production process, the system was optimized by implementing the vision library in IP, which is used to produce high speed processing FPGA-based systems and to detect defect patterns. The implemented IPs comprised of Pattern Matching IP, VGA Control IP, Memory Control IP and Single Clock Processing MAD Pattern Matching IP. Xilinx was used to process the image transmitted in high speed from Digital Camera, Vertex-4 type FPGA chip. It allowed the processing of 2352(H) * 1728(V) *8Bit image data transmitted from the camera without the need for a separate Frame Grabber Board[5] in the FPGA. In addition, it could check the image data on a PC. For pattern matching, it abstracted a 480*480 area out of the image, transmitted the image to each IP and displayed the Pattern Matching output result on a TFT-LCD.

Cheol-Hong Moon, Hyun-Chul Jang, Jin-Kook Jun
A New Technique of Camera Calibration Based on X-Target

A new technique of camera calibration based on X-target is proposed. Calibration steps include: judging gray saturation, adjusting verticality between optical axis and object surface, two-dimensional plane camera calibration. In the calibration process, the improved Harris operator and spatial moment are used to detect sub-pixel X-target corners, and the accuracy achieves up to 0.1 pixels. It does not need to calculate the specific internal and external camera parameters, and only calculates the relations of world coordinates and image pixel coordinates, and the distortion model. The method has better accuracy and stability, and has been applied in the industrial field of embedded machine vision.

Ruilin Bai, Jingjing Zhao, Du Li, Wei Meng
Application Research of the Wavelet Analysis in Ship Pipeline Leakage Detecting

Monitoring of ship pipeline leakage detecting is one of the most important techniques to be developed as it can help to prevent damages of ship working safe. Negative pressure wave technique is an effective method for paroxysmal fluid leakage detection and location. However, it is difficult to distinguish sources which led to the fluid pressure drop. In order to solve the problem, wavelet transform algorithm was adopted to define inflexion of the negative pressure wave when it propagates along the pipe, and wavelet threshold denoise technique was used to separate the characteristic inflexion of negative pressure wave when calculating the leaking position. A new pipeline detection and location system on the basis of that was developed.

Zhongbo Peng, Xin Xie, Xuefeng Han, Xiaobiao Fan
Analysis and Implementation of FULMS Algorithm Based Active Vibration Control System

Considering the passive vibration control methods are not effective for low frequencies and will increase the size and weight of the system, an active vibration control (AVC) system is designed in this paper based on the filtered-u least mean square (FULMS) algorithm. Giving the multi-in multi-out (MIMO) FULMS controller structure and taking the configured smart beam with surface bonded lead-zirconate-titanate (PZT) patches as research object, an AVC experimental platform is established to testify the effectiveness of the proposed controller. Experimental results indicate that the designed MIMO FULMS vibration controller has a good control performance to suppress the vibration significantly with rapid convergence.

Zhiyuan Gao, Xiaojin Zhu, Quanzhen Huang, Enyu Jiang, Miao Zhao
Performance Analysis of Industrial Wireless Network Based on IEEE 802.15.4a

The IEEE 802.15.4a standard provides a framework for low data rate communication systems, typically sensor networks. In this paper, we have established a realistic environment for the preliminary performance analysis of the IEEE 802.15.4a. Several sets of practical experiments are conducted to study its various features, including the effects of 1) numeral wireless nodes, 2) numeral data packets, 3) data transmissions with different upper-layer protocol. Time-delay is investigated as the most important performance metric. The results show that IEEE 802.15.4a is suitable for some industrial applications which have more relaxed throughput requirements and time-delay.

Tongtao Li, Minrui Fei, Huosheng Hu
A Hybrid Ant Colony Optimization and Its Application to Vehicle Routing Problem with Time Windows

The Ant Colony Optimization (ACO) is a recent meta-heuristic algorithm for solving hard combinatorial optimization problems. The algorithm, however, has the weaknesses of premature convergence and low search speed, which greatly hinder its application. In order to improve the performance of the algorithm, a hybrid ant colony optimization (HACO) is presented by adjusting pheromone approach, introducing a disaster operator, and combining the ACO with the saving algorithm and

λ

-interchange mechanism. Then, the HACO is applied to solve the vehicle routing problem with time windows. By comparing the computational results with the previous literature, it is concluded that the HACO is an effective way to solve combinatorial optimization problems.

Xiangpei Hu, Qiulei Ding, Yunzeng Wang
Modeling and Simulation of a Yacht Propulsion System

This paper firstly introduces the schematic diagram of a yacht propulsion system. Mathematical models of the yacht propulsion system are then proposed including main diesel engine, reduction gearbox, hydraulic clutch and propeller. The programming of simulation software and the design of simulation hardware are described. The practical operation with this training software is also introduced, which could be used for operation skill training and certificate assessment of Yachtsmen.

Yihuai Hu, Xiaoming Wang, Huawu Zhang

The Second Section: Modeling and Simulation of Societies and Collective Behaviour

Two-Phase Clock Auction Design

We propose the two-phase clock auction as a practical means for auctioning many units, a private values clock phase is followed by an interdependent values clock auction phase. The approach combines the simple and transparent price discovery of the private values clock auction with the efficiency of interdependent values clock auction. The private values clock phase is maintained as long as possible to speed up the auction process, and then is taken over to an interdependent values clock auction to improve efficiency and enhance sellers’ revenues.

Lanbo Miao, Jiafu Tang
Research on Simulation of Multi-agents Competition Model with Negotiation

To construct an artificial system with multi-Agents, it is obvious that some important factors, such as different agent’s interests, limited resources and so on, will inevitably lead to conflict. To reduce conflict, it is found that effective competition with negotiation among multi-Agents can improve overall performance. Thence, this paper proposes a new Multi-Agents Competition Model with Negotiation, which improves the forecast accuracy of opponent’s competing strategies with negotiation information and shortens negotiation time effectively depending on selecting strategies in probability to maximum interest.

Liqiao Wu, Chunyan Yu, Hongshu Wang
Synchronization of Ghostburster Neurons under External Electrical Stimulation: An Adaptive Approach

The synchronization of two Ghostburster neurons under different external electrical stimulations is considered. Firstly, the periodic and chaotic dynamical behaviors of single Ghostburster neuron under various external electrical stimulations are analysed. Then the synchronization of general master-slave chaotic systems is formulated and an adaptive controller based dynamic compensation is designed to synchronize two Ghostburster neurons. Since the adaptive controller based on dynamic compensation is utilized, the exact knowledge of the systems is not necessarily required. Asymptotic synchronization can be achieved by choosing proper controller parameters. Simulation results confirm that the adaptive control approach employed in this paper is valid in the synchronization of two Ghostburster neurons.

Wei Wei, Dong Hai Li, Jing Wang, Min Zhu

The Third Section: Advanced Theory and Methodology in Fuzzy Systems and Soft Computing

A Collision Detection System for an Assistive Robotic Manipulator

To make human-manipulator interaction safe, a method and its realization of safety design of assistive robotic manipulator based on collision detection is presented in this paper. The collision is detected by the difference of the reference torque calculated according to the dynamic model and the factual torque measured by torque sensors. In the design of the joint torque sensor, the finite element analysis is applied to determine the optimal position for pasting strain gauge, and then a signal processing circuit with high capacity of resisting disturbances is developed. According to the low speed characteristic of the assistive robotic manipulator, a simplified dynamic model is established, which balances the efficiency and accuracy of the calculation of the reference torque. Experimental results are given to prove the validity of the proposed design.

Weidong Chen, Yixiang Sun, Yuntian Huang
Adaptive Visual Servoing with Imperfect Camera and Robot Parameters

This paper presents a new adaptive controller for dynamic image-based visual servoing of a robot manipulator when the camera intrinsic and extrinsic parameters and robot physical are not calibrated. To cope with nonlinear dependence of the image Jacobian on the unknown parameters, this controller employs depth-independent image Jacobian which does not depend on the scale factors determined by the depths of feature points. By removing the scale factors, the camera and robot parameters appear linearly in the close-loop dynamics so that a new algorithm is developed to estimate these parameters on-line. Lyapunov theory is employed to prove asymptotic convergence of the image errors based on the robot dynamics. Simulations have been conducted to demonstrate the performance of the proposed controller.

Hesheng Wang, Maokui Jiang, Weidong Chen, Yun-hui Liu
An Interactive Method to Solve the Priorities of Attributes While the Preferences of Evaluated Units Are under Considering

Formerly, the preferences or attitudes of evaluated units are not under considering while the group decision methods are applied in evaluations. In this paper, a new model is proposed for solving the priorities of attributes. By simulating the decision-making process, the model uses an interactive method to optimize the priorities of attributes and determine the scores of evaluated units. An applied example given at the end of the paper shows the process of this method.

Guohua Wang, Jingxian Chen, Qiang Guo, Liang Liang
Solving Delay Differential Equations with Homotopy Analysis Method

Delay differential equations have a wide range of application in science and engineering. They arise when the rate of change of a time-dependent process in its mathematical modeling is not only determined by its present state but also by a certain past state.In this paper, a nonlinear delay differential equation in biology was investigated. The approximation solution for the model was obtained by homotopy analysis method. Different from other analytic techniques, the homotopy analysis method provides a simple way to ensure the convergence of the solution series, so that one can always get accurate approximations. Compared with the numerical solution, the approximation solution has higher precision. It is showed that the homotopy analysis method was valid and feasible to the study of delay differential equations.

Qi Wang, Fenglian Fu

The Fourth Section: Biomedical Signal Processing, Imaging, and Visualization

EEG Classification Based on Artificial Neural Network in Brain Computer Interface

Aiming at the topic of electroencephalogram (EEG) pattern recognition in brain computer interface (BCI), a classification method based on probabilistic neural network (PNN) with supervised learning was presented in this paper. It applied the recognition rate of training samples to the learning progress of network parameters, The learning vector quantization is employed to group training samples and the Genetic algorithm (GA) is used for training the network’s smoothing parameters and hidden central vector for determining hidden neurons. Utilizing the standard dataset I(a) of BCI Competition 2003 and comparing with other classification methods, the experiment results show that this way has the best performance of pattern recognition, and the classification accuracy can reach 93.8%, which improves over 5% compared with the best result (88.7%) of the competition. This technology provides an effective way to EEG classification in practical system of BCI.

Ting Wu, Banghua Yang, Hong Sun
Open Electrical Impedance Tomography: Computer Simulation and System Realization

Electrical impedance tomography (EIT) is a non-invasive technique used to image the electrical conductivity and permittivity within a body from measurements taken on body’s surface. But the low spatial resolution of imaging, complicated operation and the asymmetrical placement of electrodes make the EIT cannot achieve the requirements of clinical application. In this paper, we proposed a novel idea of open electrical impedance tomography (OEIT) and a new type of electrode to provide more valuable distribution information of electrical impedance for local subsurface biological tissues than closed EIT. The OEIT system is constructed. The electromagnetic mathematical models of OEIT are presented and a method to solving the boundary value problem of half infinite calculating region is proposed for the computer simulations. Furthermore, we have realized the OEIT system, and completed the physics and the clinical experiments. Experiment results show that the OEIT system can obtain a better resolution and positioning accuracy, and is more suitable for clinical application.

Wei He, Bing Li, Chuanhong He, Haijun Luo, Zheng Xu
Digital Watermarking Algorithm Based on Image Fusion

The process of watermarking can be viewed as a process of image fusion from the original image and the watermark image. Assuming that the watermarked image is the steady-state, Kalman filter is used as an optimal estimation algorithm in the process of image fusion. The math model is built according to the watermark image and the original image. Then the state equation and the corresponding measurement equation are built. The optimal estimation is received in the case of minimum estimation error variance. Experimental results show that the proposed algorithm has a good performance both in robustness and invisibility.

Fan Zhang, Dongfang Shang, Xinhong Zhang
The Dynamics of Quorum Sensing Mediated by Small RNAs in Vibrio Harveyi

Quorum sensing (QS)is a important process of communication, we study a mechanism induced QS by coexist of small RNA and signal molecular (AI) in this paper. We construct a mathematical model to investigate phenomenon and find that there are periodic oscillation when the time delay and hill coefficient exceed a critical value. The periodic oscillation produces the change of concentration and induces QS. In addition, we also find the this network is robust against noise.

Jianwei Shen, Hongxian Zhou
An Algorithm for Reconstruction of Surface from Parallel Contours and Its Section Contour Extraction in any Cutting Plane

To obtain reconstruction of surfaces from a given contours stack, this paper presents a new algorithm based on MC-algorithm, which solves the problem that 3D surface model cannot be built because the first/last contour has no previous/next contour information, or there are only isolated contours. Meanwhile, the algorithm is applied to extracting section contour of the 3D model in any cutting plane. The algorithm does not need to do as following: traverse and rebuild each triangle of the 3D model, obtain the points of intersection with the cutting plane, and link all points of intersection to get the contour in cutting plane. The algorithm divides the cutting plane into rectangular grid and gets isoline in each marching rectangle directly, without considering the problem of connections of all points of intersection. The 2D sectional contour can be obtained directly after finishing calculating isoline in the rectangular grid.

Chun Gong, Can Tang, Yanhua Cheng, Sheng Cheng, Jianwei Zhang
Simulation Modeling of Network Intrusion Detection Based on Artificial Immune System

There is much comparability between natural immune system and computer security, and the key point is how to distinguish self from other. Based on the principles and structures of artificial immune system, the simulation modeling of network intrusion detection was developed. The model consisted of many nodes that distributed across different locations. The nodes needed not be centralized controlled. The purpose of model was to distinguish between illegitimate behavior (non-self) and legitimate behavior (self). In case of finding abnormity, model could give an alarm to user.

Yu Jing, Wang Feng

The Fifth Section: Computational Intelligence in Utilization of Clean and Renewable Energy Resources

Organic Acid Prediction in Biogas Plants Using UV/vis Spectroscopic Online-Measurements

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes, making a reliable online-measurement system absolutely necessary. This paper introduces a novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200nm to 750nm. Advanced pattern recognition methods, like LDA, Generalized Discriminant Analysis (GerDA) and SVM, are then used to map the measured absorption spectra to laboratory measurements of organic acid concentrations. The validation of the approach at a full-scale 1.3MW industrial biogas plant shows that more than 87% of the measured organic acid concentrations can be detected correctly.

Christian Wolf, Daniel Gaida, André Stuhlsatz, Seán McLoone, Michael Bongards
Power Quality Disturbances Events Recognition Based on S-Transform and Probabilistic Neural Network

Power quality (PQ) events recognition is the most important research area of power quality control. A novel high performance classification system based on S-transform and probabilistic neural network is proposed in this paper. Firstly, S-transform processes the original PQ signals into a complex matrix named S-matrix. The time and frequency features of disturbances signal are extracted from the S-matrix. Then, the selected subset of features is used as the input vector of the classifier. Finally, the probabilistic neural network classifier is trained and tested by the simulated simples. The simulation results show the effectiveness of the new approach.

Nantian Huang, Xiaosheng Liu, Dianguo Xu, Jiajin Qi
A Coordinated Heat and Electricity Dispatching Model for Microgrid Operation via PSO

This paper proposes an optimization model for interconnected Microgrid with hierarchical control. In addition to operation constraints, network loss and physical limits are addressed in this model. As an important component of Microgrid, detailed combined heat and power (CHP) model is provided. The partial load performance of CHP is given by curve fitting method. Meanwhile, electric heater, which supplies heating via electricity, is considered in the model to improve economy of Microgrid operation. The proposed model is formulated into an mixed integer nonlinear optimization problem (MINLP). As an effective tool of nonlinear optimization, particle swarm optimization (PSO) is employed to optimize the operation schedule to minimize the total operational cost of Microgrid considering the jointly optimization of CHP, electric heater and heat storage. Result shows the availability of the proposed algorithm to the model and methodology.

Li Zhong Xu, Guang Ya Yang, Zhao Xu, Jacob Østergaard, Quan Yuan Jiang, Yi Jia Cao
MPPT Strategy of PV System Based on Adaptive Fuzzy PID Algorithm

To further improve the control quality of photovoltaic generation MPPT system, dual-mode adaptive fuzzy PID control strategy was proposed in this paper. On the basis of conventional fuzzy tracking algorithm, the principle of control algorithm was analyzed and the control system was designed. The results show that dual-mode control algorithms can quickly sense the changes in the external environment, and track the maximum power point rapidly. At the same time, oscillation phenomenon near the MPP is eliminated effectively. The proposed MPPT system represents good stability, accuracy and rapidity.

Jing Hui, Xiaoling Sun

The Sixth Section: Innovative Education for Sustainable Energy and Environment

Optimized Approach to Architecture Thermal Comfort in Hot Summer and Warm Winter Zone

According to the Fanger thermal comfort equations and the advantage of artificial immune algorithm in solving combinatorial optimization to engineering problems, the artificial immune algorithm has been applied to the thermal design and optimization of parameters for the HVAC (Heating, Ventilation, and Air Conditioner) within a building. Then, aiming at climate characteristics of high temperature and humidity in hot summer and warm winter zone, the interior thermal comfort objective function is deduced. Then, the preferable range of indoor air temperatures and air velocities which meet the thermal comfort requirements under different activities and humidity is obtained by simulation. Therefore, the relationship between indoor thermal comfort and energy saving to a building is also managed to reveal. Furthermore, it is evidence that the proposed method in this paper should be employed in the criteria for thermal design to a building and control of an air conditioning system.

Xianfeng Huang, Yimin Lu
The Application of Computational Fluid Dynamics (CFD) in HVAC Education

In this paper, we show the application of CFD in HVAC education. In the course, it was conducted using Fluent CFD software to improve the ventilation performance in one classroom. The CFD approach provided simulation results with different numbers of fans installed in the classroom. In the CFD simulations, the models with fans or without fans were created. By comparing the different cases simulated by Fluent software, it was found that installing fans could improve the ventilation performance in the classroom effectively. It also can be seen from the CFD simulation results that the numbers of the fans and installing positions of the fans can affect the ventilation performance.

Jiafang Song, Xinyu Li

The Seventh Section: Intelligent Methods in Power and Energy Infrastructure Development

Power-Aware Replacement Algorithm to Deliver Dynamic Mobile Contents

As more and more users are using wireless network to access Web contents, the power awareness issue becomes one of the most important concerns for Mobile contents delivery networks (MCDN). Unnecessary power dissipation always brings the disconnection and delay during the time of wireless access. Replacement algorithm is looked upon as one solution to resolve this problem. However, most of the current replacement algorithms have not been taken the power-awareness into consideration. Therefore, in this paper we design a new method where a novel power-aware algorithm is proposed. Both theory analysis and simulations improve that our proposal can outperform other conventional methods.

Zhou Su, Zhihua Zhang
Study on High-Frequency Digitally Controlled Boost Converter

This paper presents a completely digitally controlled high-frequency boost converter. The research focuses on the two key modules: Digital Pulse-Width Modulation (DPWM) and digital control-law. The proposed hybrid DPWM architecture, which takes advantage of Digital Clock Manager (DCM) phase-shift characteristics available in FPGA resource and combines a counter-comparator with a digital dither block, is introduced firstly, and then a digital control algorithm is designed. Finally, based on a Xilinx Virtex-II Pro FPGA board with 32MHz hardware clock, an 11-bit DPWM and a digital controller are implemented for a boost converter. The performance of the converter is validated by experimental results.

Yanxia Gao, Yanping Xu, Shuibao Guo, Xuefang Lin-shi, Bruno Allard
Backmatter
Metadaten
Titel
Life System Modeling and Intelligent Computing
herausgegeben von
Kang Li
Xin Li
Shiwei Ma
George W. Irwin
Copyright-Jahr
2010
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-15853-7
Print ISBN
978-3-642-15852-0
DOI
https://doi.org/10.1007/978-3-642-15853-7