Advances in Automation III

This paper describes the upgrade of the existing wastewater treatment facilities in the town of Mirny, which consists in adopting an automatic process control system (APCS) for the second stage of biological wastewater treatment. Upgrading the existing biological treatment process was necessary due to the qualitative and quantitative changes in households’ wastewater, as well as due to the need to adopt an automatic process control system using state-of-the-art wastewater treatment technology. The existing wastewater treatment facility design documentation has undergone major revisions regarding solutions, electricity delivery, and comprehensive automation. The paper describes the structure and computerization of the system; it also shows the automation diagrams and explains which solutions were chosen for the upgrade and why. The paper further dwells upon the development of the operator GUI. The paper also highlights the positive outcomes in the form of using less manual labor. The system is highly reliable and error-proof, as it contains an alarm system, is capable of issuing alerts, can lock the actuators in order to protect its integrity, self-diagnose the malfunctions, process data, generate and archive reports. In order to complete the implementation of the biological wastewater treatment APCS, there are plans to compose a blue paper on the tertiary treatment process that keeps suspended matter on the inner surface of self-washing disc filters. This reduces the amount of filtered particulate matter as well as chemical and biological consumption of oxygen and phosphates; as a result, wastewater fees become lower.

The article is devoted the issues of mathematical modeling of cutting processes, which today represent a rather complex and nontrivial scientific problem that requires the use the newest methods for synthesizing models based on a synergistic concept and reflecting the interconnection parameters and coordinates state of processing processes, as well as the use of modern software packages to assess the adequacy. By the synergetic concept modeling process, we mean the construction of such models that would reflect the formation reactions to the shaping movements the tool in a woodworking machine in the coordinates of the cutting process, such as processing speed and feed rate. Our goal of modeling in the work has been achieved, a model of the dynamics the cutting system has been developed in two versions, the first option takes into account only the moments and forces associated with the formation of the cutting force in the processing zone, and the second model includes an additional moment of resistance associated with the accumulation of chips in the chip channel drill. The paper presents the results of modeling the obtained models in the MATLAB environment, these results confirm the adequacy of the developed models.

This study analyzes modern hardware solutions for high-performance data processing. High performance of computing systems is achieved by using appropriate architectural solutions and modern electronic devices, which are constantly being improved and modernized. The tables provided in this study describe the latest high-performance computing and storage systems. Modern hardware solutions have been analyzed that break the exaFLOP barrier. Problems associated with achieving super high performance have been formulated.

We posed a problem and developed an algorithm for the neural network parametric identification of nonlinear dynamic models of objects with a computational experiment, the formation of training samples on its basis and the subsequent sequential training of two neural networks. Neural networks perform bijective mapping of object parameters into the original model to the output variables of the second neural network. Sequential training or sequential bijective identification of a neural network consists in preliminary training of the first neural network based on experimental data and using its synaptic coefficients to train the second neural network. An example of parametric identification of a nonlinear dynamic model will be a 600 W high pressure sodium lamp. The computational experiment was carried out in the MATLAB environment. The computational experiment technique and the results of experimental studies are presented in the article. Taking into account the good approximating ability of neural networks, the proposed algorithm can be considered as an effective method for parametric identification of nonlinear models.

This paper substantiates methods of applying the theory of statistical hypotheses in tasks of automating technological processes. Automated system operations are considered to be multi-alternative in terms of the theory of statistical hypotheses: two hypotheses of the correct mode and two hypotheses of the erroneous operation of the system. This paper provides general expressions for calculating the probabilities of these modes for two statistical models of the controlled parameter of the technological process and standard models of the metrological spread of the measuring channel. Herewith the accuracy class of the measuring channel should be expressed as a reduced error. A program has been developed for the statistical evaluation of the operating modes of the automation system for symmetric and asymmetric statistical models of the controlled parameter spread and several models of the metrological evaluation spread of this technological parameter.

The article provides an overview of the existing methods of metrology use in the control of the accuracy of manufacturing processes. The choice of using the 3D-scanning procedure for metrological control of parts manufactured using additive technologies is justified. The article provides an example of using the 3D scanning method for metrological control of a part. A structured-light 3D scanner was used as a measuring tool. The article describes the method of using a 3D scanner to calibrate a 3D printer to compensate for the shrinkage of various materials: PLA, ABS, PETG, Nylon. For metrological control, a part with a complex geometry was selected, namely, a centrifugal turbine impeller printed by an FDM printer. A comparative analysis using measured material shrinkage coefficient was carried out on a centrifugal impeller. The article also describes the effect of supports on the curvature of the impeller blades. The study of the influence of the printing speed and the layer height on the accuracy of the part manufacturing was carried out.

The article is devoted to the development of a control system for a Virtual Power Plant (VPP) with distributed generation (DG). The general principles of VPP functioning are described. A multi-agent approach to the VPP management that combines DG units, storage units and electricity consumers using a Solid-State Transformer (SST) is proposed. Many agents have been introduced for VPP facilities. The agent interaction principles for the implementation of the VPP intelligent management system have been developed. On the basis of simulation modeling in the RastrWin and Jade software complexes, a study of the effectiveness of using a multi-agent control system for the considered VPP has been conducted. As a result of the first iteration, the use of a multi-agent control system enabled to reduce power losses in the electrical network and increase the utilization rate of the installed capacity of power plants that are part a part/parts of the VPP.

The paper discusses a hypergraph model of the mechanical structure of a technical system. The model describes the coordination of parts during assembly of a product, obtained by basing on design bases. This model correctly describes the operations and assembly processes of products that have the properties of sequentiality and coherence. The sequential and coherent assembly operations are prevalent in the assembly of modern technical systems: machines and mechanical devices. In terms of this model, the assembly operation is represented as a normal contraction of an edge. The sequence of contractions that transforms the hypergraph into a point is a mathematical description of the assembly process. A theorem on the necessary conditions for contractibility of hypergraphs is presented. It is shown that the necessary conditions are not sufficient. An important theorem on sufficient conditions of contractibility is proved. The concept of an ns-hypergraph is introduced. Ns-hypergraph is a mathematical model of the mechanical structure that cannot be assembled due to structural defects. Computational experiment was carried out to enumerate the ns-hypergraphs of various orders. The proposed apparatus can be used in computer-aided design systems for structural analysis of complex projects and computer-aided planning of assembly processes.

The paper proposes an approach to creating an automation system for controlling and monitoring the climatic conditions of a production facility, which is characterized by the use of available microprocessors and mass-produced components. The developed system, including all its software and hardware components, should be flexible in terms of construction, use and readjustment, should be close to analogs existing on the market, such as climate control elements for building automation systems, but have greater functionality and lower cost. The development of such a solution will increase their availability and flexibility by expanding the technology stack applicable to solving such problems.

This paper considers the problem of the control system transient process quality improvement, which is very important in thermal engineering even now. The way of improvement under consideration is the use of a predictive control algorithm. The control algorithm described is a PID control law with a first order filter and a linear prediction module; the control system is also equipped with an auto-tuning module, that allows to retune the system if necessary. The auto-tuning module uses a fast auto-tuning algorithm calculating the process model parameters using the process reaction of a rectangular impulse. The PID algorithm coefficients are calculated using indirect optimality indexes. The system works with a typical thermal process with a second order transfer function with a time delay. Calculations and simulation of the system are carried out in Mathcad and Matlab/Simulink. Some examples are considered, the predictive control system performance is estimated and recommendations on the prediction time interval determination are given. These recommendations may be further used while developing this system using modern controllers and controller programming software.

This paper presents the development and study of a model for formalizing the process of making a diagnosis using artificial intelligence methods. Currently, various artificial neural networks and expert systems have been created and are used for diagnosis. Analysis of these works has shown that these methods show good results, but have a number of drawbacks, the most significant of which is the complexity of organization and the significant time required to train a neural network. Thus, the problem is to develop new algorithms that have a probability of making an accurate diagnosis, comparable with artificial neural networks and expert systems, while having a shorter training time. One of the ways to solve this problem is to develop a model for diabetes diagnosis based on an artificial immune system. The purpose of this work is to develop and study of a model for formalizing the process of diagnosis using methods of artificial intelligence. The paper reviews a model of the diagnosis process: pre-diabetes (impaired glucose tolerance, impaired fasting glycemia), type I diabetes, type II diabetes. The problem of diagnosing the disease can be regarded as a classification problem. In this paper, the process of diagnosis was examined as a division of test data and patient history into four classes corresponding to one of the diagnoses: pre-diabetes (impaired glucose tolerance, impaired fasting glycemia), type I diabetes, type II diabetes. An artificial immune system and Kohonen artificial neural network were used to solve this problem.

The paper researches the regularities of functioning processes of the multiposition conveyors which are widely used in industry. The process of manufacturing systems’ functioning is characterized by a significant degree of uncertainty and is influenced by many accidental factors. The working efficiency of the manufacturing systems under study in many respects is determined by arranging the process of multiposition conveyor’s functioning. The main factors, determining the conveyor’s efficiency, are brought to light. The objective of the current research is the identification of the main factors, deter-mining the efficiency of the multiposition conveyor, and the analysis of the character of the conveyor’s efficiency dependency on the exposed factors. To evaluate the influence of reliability parameters of a multiposition conveyor on the efficiency of a flexible manufacturing section a mathematical model was developed.

The dynamic and static defect models for rotor mechanical assemblies have been compared in the article. The article gives reasons for the significance of dynamic modeling to define remaining assembly life. The article points out that it is feasible to use empiric data as a foundation for creating models. The article gives the example of a small gear defect dynamic modeling for a complete wheelset. The approximate amount of work on creating dynamic models has been defined in the article. The article proposes the methods for implementing dynamic defect models.

Preparing homogeneous compositions from various materials and mixing them is a widely used process in food industry. The quality of the finished product often depends on the process. Increasing requirements for the quality of mixtures demand the need for studying the performance characteristics of various mixing equipment types. One of these approaches is mathematical modeling. In this paper, we consider the simulation of a spiral dispenser operation, providing a preliminary initial stage of high-quality components mix. Fluctuations in the dispenser lead to stochastic changes in its output signal, which in turn complicates the modeling process. To solve this, we use sequential structural transformations of the signal to filter fluctuations, and the continuous fractions apparatus to construct a mathematical model of the dispenser output signal in the form of a harmonic component with a certain amplitude and a circular frequency. The highly accurate results achieved allow us to simulate the processes at the input of continuous-type mixers, evaluate the efficiency of mixing processes and assess the impact of technological parameters on the quality of mixtures.

The paper discusses the forthcoming exploration of gas giant’ satellites in our Solar system, that will become important for humanity in the near future. In the entire history of cosmonautics, less than 10 spaceships have been directed to gas giants’ planets in order to study their satellites. All these flights were unmanned, and there were no sample capsule returns. All information came through a network of communication satellites. This information indicates many promising satellites for exploration and colonization. The reason for a poor study is the huge distance between our planet and gas giants. The development and construction of a spaceship for astronaut’s flights and scientific equipment is a difficult and expensive task. To deal with this task we should preliminarily use computer modeling. The software that we propose for this is the Kerbal Space Program 1.7. The current paper was designed based on this program, which is very beneficial for the development of “space” literacy, especially for young people. The tasks of this research are differed and cover the choice of a flight trajectory and types of spacecrafts and equipment needed for satellites exploration. The algorithm for project realization is shown, and steps of its implementation are described by simulation.

The paper deals with the problem of determining the parameters of the transported gas in case of partial destruction of subsea sections of gas pipelines. The solution to this problem is proposed to be obtained on the basis of creating a mathematical model describing the relationship of pressure, velocity and gas temperature at each point of the subsea main pipeline, including at the place of emergency outflow. To build such a model, the equations of the continuity of the gas flow in all sections of the gas pipeline, the equations characterizing the change in the momentum of this flow, as well as the equations of heat content for the molar gas flow rate for the pipeline sections before and after the rupture were used. The process of submerged gas outflow through a partially destroyed pipeline wall is considered as an adiabatic process obeying Saint-Venant's law and occurring at the local speed of sound. For the case of the location of the rupture in the deep-water section of the main pipeline, a mode of subsonic gas outflow is provided as its adiabatic movement through a short pipe without friction. A numerical check of the performance of the proposed model was carried out for a subsea gas pipeline with a variable profile. Quantitative distributions of the characteristics of the gas flow along the main pipeline with fractures with different areas are also obtained. The combination of these distributions makes it possible to automatically identify the parameters of emergency gas outflows in subsea gas pipelines. According to the values of gas pressure, velocity and temperature at the inlet and outlet of the controlled section, the area of local destruction of the main pipeline and the location of the rupture on the route are calculated. These parameters make it possible to form such a control of the compressor stations, which is adequate to the current abnormal state of the pipeline.

The article shows that accurate models for determining the cost of services for the reduction of power losses in a network organization with reactive power compensation (RPC) in a consumer network did not exist for a long time. The development of such models will help to increase the quality of the state management in terms of compensating the consumer for the costs of installing and operating compensating devices (CD). Currently, in order to carry out a feasibility study for the installation of a CD of a certain capacity, the consumer can use, depending on the capabilities, a mathematical or a programme model, or a polynomial model proposed in this article. The creation and the improvement of the model are associated with the need to activate consumers in terms of the PRC.

Reliability of electricity supply is the main and most important task of the energy industry in Russia. With the introduction of new equipment, such as gas turbine and combined cycle plants, the problem of effective energy saving becomes an important component. At the moment, it can be solved by increasing the efficiency of generating equipment. This article discusses the possibility of using a vapor compression unit, an absorption refrigeration machine in the cycle of a thermal power plant. The main energy characteristics of the equipment, advantages and disadvantages are considered. A comparison of absorption chiller and vapor compression unit is considered.

The article is devoted to the numerical simulation of a perovskite solar cell with the FTO/TiO2/CH3NH3PbI3-xClx/Cu2O/Me structure in the SCAPS-1D program. The effect of the thickness and defect concentration in the perovskite layer CH3NH3PbI3-xClx, as well as the work function of the back contact material (Me), on the photoelectric characteristics of a solar cell has been studied. It was found that the optimal thickness of the CH3NH3PbI3-xCIx layer is 600–700 nm, and the defect concentration should be less than 1014 cm−3. It is shown that the work function of the back contact material must be greater than or equal to 5 eV to create solar cells with high efficiency. A maximum efficiency of 21.55% was obtained (short circuit current 24.87 mA/cm2, open circuit voltage 1.1 V, fill factor 78.82%) for the structure of a perovskite solar cell with a carbon (C) back contact. The results can be used in the design and manufacture of efficient and inexpensive perovskite solar cells.

The article considers a new approach to combinatorial and logic graph problems, which belong to the class of NP-complex optimization problems. To address them effectively, the authors have suggested a new strategy based on the integrated approach. A distinctive feature of this approach is a division of search process in several levels. At the first level, areas with a high value of the objective function are allocated by an artificial bee colony optimization method. At the second level, the obtained results are improved by evolutionary and genetic algorithms. To implement this approach, it is developed an integrated search architecture, which can obtain sets of quasi-optimal solutions in polynomial time. As an example of the combinatorial and logic graph problem, a partitioning of elements can be given. The authors have suggested an evaluation function as a ratio of the total number of internal edges to the total number of connecting edges. A software application has been developed on the C#. A computational experiment has been carried out on the basis of IBM benchmarks. Conducted experimental investigation have shown that the quality of solutions obtained by the integrated approach on average exceeds the quality of solutions obtained by hMetis and PGAComplex by 5–7%. The time complexity of the developed integrated approach is O(n2) in the best case and O(n3) in the worst case.

This article considers the implemented means of modeling and recording the parameters of technological processes, documentation, and support of the life cycle of radiopharmaceutical production. Simulation tool (imitator) is a hardware-software complex for recording, storage, and analysis of data on the technological process of radiopharmaceutical production. The purpose of the functioning of this system is also the automation of production processes of forming accompanying documentation, control of production processes. The means of ontological support make it possible to identify possible risks in the production processes of radiopharmaceuticals, based on partially entered indicators and previous checks, as well as to form a database of precedents to ensure compliance of the manufacturing process with regulatory documents, information support and recording of technological parameters during manufacturing, including document flow and process control is necessary. For this purpose, a new information system for recording technological process parameters, documentation, and support of the radiopharmaceutical production life cycle was developed.

Process analysis and optimization is impossible without simulation. Models make it possible to represent and visualize the main interrelationships between the individual stages of the process, to investigate and predict the course of its development, to find bottlenecks and the ways of modernization. One of the important tasks in process optimization is the analysis of its structure, since various options for its organization impose corresponding restrictions on the possibility of its rebuilding. This paper discusses the issues of structural analysis of processes: the definition of linear structures, branches and cycles. Algorithms for the automatic analysis of the process represented by the extended Petri net with semantic relation are developed. An example of searching for such structures in the process of repairing a truck is considered.

At some of industrial enterprises, electron-beam welding technology is used in processes requiring the formation of permanent connections between equipment elements. However, its application is complicated by the need for accurate selection of the values of technological parameters. The software system proposed in this work allows simulating the temperature distribution over the volume of the products to be joined in the process of electron beam welding. The theory of welding processes is used as a mathematical apparatus. The software system has a modular structure and consists of six subsystems that implement specific functionality. All data, both input for mathematical models and results are stored in a single database, consisting of nine joined tables. The use of the proposed software allows both to reduce the cost and simplify the process of adjusting the technological parameters of electron beam welding, and to form the basis for the further implementation of effective control systems.

This article highlights the power systems digital twins development and application, and also proposes digital twin architecture along with the digital twin software implementation prototype. The digital twin is a key building block of a high-tech control system. The energy system digital twin is considered as the main tool for high-tech distributed energy infrastructure intelligent management. As an example of the digital twin application, it is given the hybrid power supply system optimal configuration calculation. Also, a power system active low voltage consumer software implementation prototype digital twin based on the products Nrjpack, Matlab Simulink and Homer PRO was performed.

The numerical simulation model of the slag mode control and diagnostics system contains the following calculation blocks: determination of yield, composition and polytherm viscosity of final slag; calculation of slag desulfurizing ability; slag mode diagnostics. The model is applicable to slags with permissible variations of Al2O3 content from 3 to 17%, MgO - from 5 to 20%, SiO2 content of 35% and more in slags, CaO content of 35% and more in slags. The developed automated information system calculates the following slag properties: slag temperature, slag viscosity at slag discharge temperature, slag basicity (CaO/SiO2), (CaO + MgO)/SiO2 and (CaO + MgO)/(SiO2 + Al2O3); temperatures at which slag viscosity is 7 and 25 poise; slag viscosity gradients in the range of 7–25 poise and in the range of 1400–1500 ℃. The system can be used by a process team both during blast furnace smelting to control and diagnose the slag mode for a selected time frame, and during simulation of slag properties with regard to the specified rates and properties of the loaded burden.

At present, global models describing the dynamics of the atmosphere, such as GFS, NAM, ECMWF, UkMet and others, are actively used to compile weather forecasts. Modern global models make it possible to build weather forecasts of a sufficiently high accuracy. Nevertheless, for local territories, errors often arise related to the peculiarities of a particular area. It is rather difficult to provide the proper level of detail for global models - it is necessary to set an extended description of the territory for the entire model, which is quite difficult (especially for poorly explored areas). At the same time, the volumes of the initial data increase and the complexity of the calculation algorithms increases. For this reason, the use of adaptive models that allow adjusting forecasts from global models for specific territories seems quite attractive.

The work is devoted to assessing the reliability of the attachment to the fuselage of aircraft engines, which directly determines the safety and reliability of the aircraft. To do this, the choice was made of the rational design of the front span. Comparison of design options and the selection of the most preferred of them were based on the chosen criterion. The choice of the variant of the scheme was carried out in order to minimize the weight of the optimized unit. The criterion function value was calculated using the End Elements Method (ICE) in the COSMOS program in SolidWorks (CAE). Tensions, loads and deformations were calculated. The results of calculations for the spangot were also verified using COSMOS. As a result, the divergence of the results of theoretical calculations and calculations COSMOS was no more than 1.2%.

In the modern aerospace industry, there is an intensive development of computer technology. This paper discusses the effectiveness of the automated design system of the Russian firm ASCON’s automated design system for the technical design of aviation parts.

In this work, studies are carried out the emission of electromagnetic interference from the secondary power supply of the unmanned aerial vehicle power system. An approach to predicting electromagnetic emission from a secondary supply and its influence on the operation of onboard equipment is proposed. A practical example of predicting the emission of electromagnetic interference from a secondary power supply, which is located on board an unmanned aerial vehicle, is discussed.

The article analyzes popular SaaS services based on the organization of customer support channels. The main “strengths” of the customer service for these SaaS projects are shown, and several positions are noted that should be improved. Also, based on the analysis, a rating of popular SAAS services was built based on the used customer support channels using the non-compensatory threshold aggregation method. The calculation was carried out in the developed software.

At the stage of the technical products’ production planning, the key point of the success for meeting the customer’s expectations is to determine customer’s needs and to convert these needs into product characteristics, which are eventually reflected in the formed product quality indicators list. To monitor quality indicators at the production stage manufacturers often use the theory of fuzzy sets to combine several groups of quality indicators into one indicator, which simplifies the process of monitoring and evaluating product quality, but complicates the process of interpreting these indicators on the principle of “acceptable – not acceptable”. To solve the problem of interpretation, an updated list based on fuzzy sets should contain not only information about the types of quality indicators, but also information on evaluation or measurement scales for each product quality indicator. In this paper, we propose a method for forming a gradations scale for product quality indicators based on fuzzy clustering. A method for forming a rank scale used for particular indicators in a two-level product quality optimization model is developed and justified. The proposed method of a fuzzy term set constructing allows to solve the problem of determining an updated list of fuzzy quality indicators.

Unmanned aerial vehicles (UAVs) are widely used in various sectors of the national economy. Therefore, improving the efficiency of algorithms for controlling the angular position of aircrafts is relevant. Predictive model algorithms based on the optimization of the generalized work functional are characterized by good computational efficiency. The paper presents a simulation of angular velocity control of an axisymmetric aircraft based on the predictive model. It is shown that disturbing moments lower the quality of control – there appear errors that can not completely eliminated by the control. The structure of combined control is proposed. It includes the main control loop using the predictive model method and the perturbation moment compensation loop. The compensation is determined based on the estimates of the disturbing moments. The estimates are obtained using predictive model algorithm. The results of modeling are presented, confirming the increase in the efficiency of control in the conditions of disturbances – the accuracy of regulation increases.

The work is devoted to the task of developing means of operational communication for intelligent transportation systems under unstable cellular coverage. A study of current trends in the development of intelligent transport systems field is carried out, an example of a prototype of the developed on-board radio-electronic device is shown. The manufactured device is installed on vehicles of civil and special purposes (including emergency, rescue and utilities), and is intended to provide an online communications service by organizing a dynamic communication network between moving cars in the presence of a partial or complete absence of traditional radio communications. Areas and scenarios of the possible application of development are considered, the most promising functions related to road safety, operational interaction of vehicles with special services, prevention of traffic jams are described.

This study uses the machine learning algorithm of decision tree classification to determine the features most useful for predicting overall productivity of an ice hockey player in an NHL (National Hockey League) season. While most existing studies use detailed data on a small number of players, this analysis is performed using a publicly accessible dataset consisting of data from 44 NHL seasons. The simplicity of the used algorithm allows to directly determine the most important features used in prediction. The results indicate that the number of assists per game has a significantly higher impact on the player’s productivity during the season and that the player’s experience and body weight are useful factors in predicting his productivity level. Our analysis shows that limited publicly accessible data contains features that can be useful in predicting a player’s productivity with average accuracy. However, more detailed data, which is usually only collected during specific trials, would be necessary to provide more practical application.

The paper considers the problem of determining the optimal daily energy consumption of an enterprise. By solving this problem, a reduction of electricity costs can be achieved by reducing energy consumption during periods of high prices, increasing energy consumption during hours when electricity prices are lower, as well as by cardinally reducing energy consumption during peak load hours. To determine the optimal daily energy consumption, three different optimization methods are proposed – linear programming method, genetic algorithm, and particle swarm optimization algorithm. The results are provided regarding the solution of the problem using the specified methods and specific input data, as well as data on actual and forecasted electricity prices. The study includes an estimation of savings obtained using various optimization methods. The effect of forecasted prices and price volatility on the size of savings is investigated as well. The methods for determining the optimal daily energy consumption discussed in this study can be useful for enterprises that pay for electricity at market prices.

The paper developed a nonlinear regression model under initial Z-information. The information received from experts has a certain level of reliability, therefore, to study dependencies and predict such information, is necessary apparatus regression analysis, that takes this reliability into account. However, the development of such apparatus is at an initial stage, therefore, research in this area is relevant and in demand. In the paper, we assume that the components of the initial Z-numbers are the values of full orthogonal semantic spaces. Operations on Z-numbers and distances between them are determined based on their aggregating points, which are the midpoints of aggregating segments. The aggregating segments for Z-numbers are defined as the aggregating segments of the product of both components. The optimization function is defined as the sum of the squares of the distances between the model Z-numbers and the initial Z-numbers and between the first components of the model Z-numbers and the initial Z-numbers. The choice of such an optimization function was made to enhance the influence of the first components of the initial Z-information. To determine the unknown regression coefficients, the minimum of the optimization function is found. The new developed model expands the possibilities of regression analysis and allows you to construct a prediction and investigate dependencies using Z-information, which is shown by the numerical example given in the paper.

In this paper the comparative analysis of student performance during face-to-face and distance learning under Z-information is developed. Importance of similar researches has increased in the context of pandemic, when the quality of education has decreased due to the enforced transition of the majority of universities to online learning. Moreover the reliability of the students’ grades has been affected negatively, which cannot be ignored. For this purpose an instrument for the processing of Z-information is essential. Student performance is associated with four Z-numbers, the first component represents the formalization of grades “unsatisfactory”, “satisfactory”, “good”, “excellent”. The formalizations of these grades constitute the valuation of a linguistic variable with the completeness and orthogonal properties, which aggregates the linguistic variables by three regulating criteria. The second component of Z-numbers is the fuzzy value of the reliability of formalized grades. Students’ performance manifests itself through the total of four Z-numbers for a term of face-to-face learning and for a term of distance learning. To conduct a comparative analysis of the collected data operations with Z-numbers, distances between them and the distance between the populations of Z-numbers are specified. A numerical example is given demonstrating the function and effectiveness of this model.

Today the most functional complex control and measurement system (CMS) is one used in intensive care units (ICU). However, the problem of compact and informative work results presentation of the control and measurement resuscitation complexes is still relevant. Problems include the low sensitivity and discriminative ability of existing patient assessment scales. There also are data problems such as limited time for obtaining, processing, analyzing and interpreting. Another problem is the lack of a unified approach to determining the patient’s condition dynamics (PCD), and the large amount to be transformed and visualized data. The article is devoted to identifying the problems of automated PCD assessment. The main goal of the study is to develop a methodology for PCD automated assessment. The methodology includes eight stages: the initial stage is the research tasks formulation, the final stage is the results visualization. The developed methodology is the basis for the automated program. This program will help to significantly facilitates and accelerates the diagnosis process, patient dynamics assessment and outcome prediction. The software was tested on the clinical data taken from patients having peritonitis.

The work is devoted to the concept of decision synthesis within the components as a part of technical systems of intelligent data processing. A methodology of experimental research aimed at substantiating the scientific and practical significance of this concept has been developed and implemented. As an object of research, we used a computer model of the component of decision-making, which provides a pattern recognition procedure based on data obtained about an external analyzed object. The results of the research represent the response of the object to changes in external conditions that affect the formation of the decision. It was revealed that the incorporation of the principles of decision synthesis into the object of research promoted the emergence of cognitive mechanisms in the process of information processing, which led to an increase in the adaptive abilities of the technical system to change the external conditions of its existence.

The article discusses the main problems of timely detection of defects in sheet metal by means of technical vision. In the course of the analysis, it was found that artificial neural networks of a typical structure do not allow to reduce the influence of real production factors on digital flaw detection images, and the quality of defect detection will be quite high. Created on the basis of a system of neurons second set and a special structure, and developed specialized algorithms based on the established network. In the course of experimental studies, defects in sheet metal were successfully identified in 89% of the images of the test set.

The article considers the issue of increasing the level of security of industrial automated systems by automating the training of users to respond to information security incidents. A software package for training users to respond to information security incidents in industrial automated systems is proposed. The article presents an overview of the information security state in industrial automated systems: the damage from cyber threats, types of attacks and objects of attacks in industrial automated systems, confidential information of the attackers’ interest. The study examined the impact of the users’ information security knowledge level on improving the quality of users’ response to information security incidents to increase the level of industrial automated systems security and prevent information security threats. 4 classes of attacks were investigated: 1) attacks using malicious software, 2) DoS-type attacks, 3) attacks using social engineering methods, 4) credential matching attacks. The results of the study and experimental data confirm the effectiveness of the proposed software package, which made it possible to increase the industrial automated system security level by an average of 28%.

In the modern world automation technologies of industrial processes have found wide application. Automated process control systems have become an important part of enterprises that operate in different economic fields and life support facilities all over the world. Nevertheless, the high growth of automation means raises the acute problem of providing APCs information security from external and internal threats. There are systematic reports in the media about new critical vulnerabilities in industrial equipment and attacks based on the exploitation of such vulnerabilities. When designing such systems it is necessary to estimate possible information security threats that already exist in the system or that are predicted to appear. That is why threat modeling is an important part of providing information security at industrial facilities using automation. In this work the author investigates the methodology of estimating threats to software security TRIKE. The research is aimed at finding general approaches to determine threat sources, tactics, and techniques for making implementation scenarios of threats to software information security, for applying them to provide cyber security of automated process control systems. In the frameworks of the subject mainstreaming, the research gives a description of cyber-attacks at big industrial facilities, and their basic vulnerabilities are emphasized. In the article the analysis of TRIKE methodology has been done. It is aimed at determining basic threat modeling stages applicable to industrial automation systems. The approach of TRIKE methodology to generating a list of threats to information security is formalized. To achieve the aims the author constructs DFD data flow diagrams with the decomposition of peculiar elements of the algorithm for modeling threats to information security of automated process control systems using TRIKE methodology.

Nowadays, industrial control systems are becoming more digital, more complex, and more interconnected causing growing anxiety about their safety, security, and especially cybersecurity. For dealing with all security problems including cybersecurity assessment, security programs are utilized where the properties of confidentiality and integrity are characterized in detail. But the availability attribute often suffers due to a lack of attention, which makes the assessment of availability grow into one of the thorniest issues. The article investigates cybersecurity in the industrial control systems context, clarifies the great value of availability, and explains a reasonable shift between cybersecurity and availability assessment problems. A delay of the signal transmission is discovered to be a suitable measure of the quantitative availability assessment, and a theory of deterministic queuing systems Network calculus is advocated to be a relevant tool for the delay estimation and availability modelling. A reference model for the availability assessment and also an appropriate metric based on delay and system dependency are proposed. The results of the verification of the applicability of Network calculus to solving the delay estimation and cybersecurity assessment problems are presented.

The article is devoted to the study of the efficiency of arithmetic operations with points of an elliptic curve using the residue number system. Based on the obtained data, it was found that the use of the residue number system with moduli of a special type from the operations with an elliptic curve from NIST FIPS 186 allows gaining 7.72% for the operation of addition and 7.50% for the operation of doubling points of an elliptic curve on average.

This article proposes the architecture of a diagnostic data mining software system for data storage systems. Analysis of logs consists of several stages: extraction of metrics from big data storage diagnostic information using artificial neural networks, analysis of time series anomalies for diagnostic data metrics using machine learning methods, generalization of the results of the analysis of anomalies and patterns of change and existence of storage performance metrics based on the characteristics of the subject area using a subject ontology, the inference of the recommendation to the administrator for correcting the storage system state through the composition of the results of the analysis of anomalies and subject ontology. In the article, an effective solution (software or algorithm) is found for the implementation of each stage. In the future, it is planned to develop this system and evaluate its effectiveness during experiments.

Oil extraction by the artificial lift method leads to the formation of asphalt, resin, and paraffin wax deposits (ARPD) in well tubing. Narrowing of the useful pipe cross-section decreases the well flow rate and increases the power consumption of the electric centrifugal pump. Therefore, cleaning of well tubing from paraffin wax is a routine procedure, which is most often performed mechanically using special cleaning devices—scrapers. This method has many advantages, though sometimes scrapers might jam in the well, or the scraper wire might slacken or break off. To ensure the fully automatic operation of such units, they shall have an automatic diagnostic system, which evaluates certain indirect signs to identify any problems, and performs the necessary actions as per a preset algorithm. This study proposes a diagnostic model of the paraffin wax cleaning device based on the results of an active experiment at the operating oil well, as well as the diagnostic algorithm allowing to increase the reliability and control of the dewaxing unit.

Commercial accounting is carried out at all stages of delivery of the produced and prepared oil to the final consumer. The most common are dynamic methods, direct (mass) and indirect (volume-mass). As a rule, accounting is carried out by systems for measuring the quantity and quality of oil (SIQO). In the process of accounting, the work of SIQO is influenced by a large number of external factors that cause the appearance of additional errors. When accounting for crude oil, wax deposition on the inner surfaces of meter lines and flow meters becomes significant. The influence of this factor in practice is not taken into account due to the immeasurability of the thickness of the paraffin layer. The article discusses the effect of paraffin on the metrological reliability of an ultrasonic flow meter. It is proposed to automatically estimate the current value of the thickness of the paraffin layer by the model and determine the value of the additional error. This allows, when approaching the limits of metrological reliability, to timely carry out maintenance of the flow meter and extraordinary control of its metrological characteristics and, in general, to increase the accuracy of accounting.

This article proposes a model of a distributed information system with the possibility of dynamically distributing the functions performed across the physical nodes of the system by changing its structure. The model is based on a matrix representation of the physical and logical structures of the system and the procedure for establishing correspondence between them. Restrictions are introduced, the observance of which is necessary for the formation of a set of equivalent transformations. The implementation of the proposed model is based on the theory of multi-agent systems. The main provisions of this theory, the types of agents used, and their structure are described. The properties of mobile agents as the main tool for implementing the model are described. A fuzzy relational model is proposed as the basis of the implementing agent. It is proposed to use a vertically organized architecture of a multi-agent system. The application of the proposed model in the construction of distributed information systems for various purposes, in particular, systems for monitoring the state of industrial facilities, will increase their reliability and safety.