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Module Name: |
Module 12: Support of the Experiment |
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Code |
M12EPE(Ma) |
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Module Elements: |
Elective subjects Theory of Simulation and Scientific Experiment Wavelet Theory Application of Microprocessors in Electric Power Systems Microprocessor-Based Automatic Control Systems Digital Automation and Control Systems in Electric Power Engineering Information Technologies in Electric Power Engineering Network Technologies Elements of Artificial Intelligence in Technical Systems System Simulation Intelligent Measuring Instruments Systems of Computer Mathematics Visual Simulation Systems Automated Data Collection Systems
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Semester Number: |
2 |
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Person responsible for the module |
A.A. Savostin |
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Lecturer: |
Theory of Simulation and Scientific Experiment — A.I. Poleschuk Wavelet Theory - A.A. Savostin Application of Microprocessors in Electric Power Systems - D.V. Ritter Microprocessor-Based Automatic Control Systems - D.V. Ritter Digital Automation and Control Systems in Electric Power Engineering - D.V. Ritter Information Technologies in Electric Power Engineering - A.I. Poleschuk Network Technologies - D.V. Ritter Elements of Artificial Intelligence in Technical Systems - A.A. Savostin System Simulation - A.A. Savostin Intelligent Measuring Instruments - A.I. Poleschuk Systems of Computer Mathematics - A.A. Savostin Visual Simulation Systems - A.A. Savostin Automated Data Collection Systems - A.A. Savostin |
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Language: |
Russian, Kazakh |
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Curriculum relation: |
Electrical Power Engineering (Ma) |
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Type of teaching / number of hours per week and per semester :
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2 semester: hours per week – 30 (lectures -6; workshops -6; independent work -18); hours per semester – 300. |
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Workload: |
Teaching Load: 180 hours Extracurricular Classes: 270 hours Total: 450 hours |
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Credit Points: |
15 ECTS |
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Conditions for Examinations: |
For admission to the exam, the master’s student must score at least 50 points out of 100 available for each subject of the module |
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Recommended Conditions: |
Module: Organizing of Scientific Research |
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Expected Learning Outcomes: |
Know: methods of experimental and computational and theoretical research; principles of modeling, methods of representation of models of control systems for industrial use; principles of the solution of technical problems of measurements with the use of modern hardware and software, architecture and algorithms of functioning of universal measuring interfaces, universal languages; special languages; simulation environments; theoretical and practical aspects of obtaining, formalization and structuring of problem knowledge; technologies and means of information processing and evaluation of results in relation to the solution of professional problems; general issues of construction of measuring systems using modern computer technology; principles of solving technical problems of measurement with application of modern hardware and software architecture and algorithms of universal measuring interfaces; methods of preparation of experimental studies and processing of the obtained results; tools such as MathCAD, MATLAB, LabVEIW for processing of experimental data; universal languages; specialized languages; simulation environment; methods and facility of computer simulation of systems; classification of artificial intelligence systems (AIS), models of knowledge representation, output solutions and communication models in AIS; theoretical and practical aspects of obtaining, formalization and structuring of problem knowledge; technology and means of information processing and evaluation of results in relation to the solution of professional problems; basic theoretical information on the problems of artificial intelligence, applied models and methods of their analysis and building skills and abilities. Be able to: use the methods of digital signal processing; organize research and production work; determine the optimal level of power loss in electrical networks by the criterion of minimum cost of power transmission, as well as to apply the methodology of step-by-step optimization of electrical networks by topological and regime properties; use the knowledge gained for the original development and application of ideas in the context of scientific research; choose numerical methods for modeling electrical power systems or develop a new algorithm for solving the problem; to calculate and analyze schemes in various systems of computer mathematics; to see ways of optimization at various stages of design; to simulate in simulation environments; build mathematical models for analysis and optimization of objects, to select numerical methods for their simulation or to develop a new algorithm for solving the problem; conduct calculation and analysis of schemes in various systems of computer mathematics; to model in simulation environments, to formalize and to structure the problem of knowledge. Possess the skills: extension and deepening of knowledge required for everyday professional activity and further education in doctoral studies; use of modern systems of data processing and collection during the technical experiment; design of controls for electrotechnological processes and equipment; use of microprocessor-based automatic control systems; apply modern systems of data processing and collection within the technical experiment; mathematical simulation in the study of power systems. Demonstrate the ability: in the analysis of the state of the power system and methods of regulation of its modes; in the design of electric drive control systems; in the application of the mathematical apparatus of wavelet transform; in the field of synthesis of digital control systems using modern engineering design software, digital automation and control systems in the electric power engineering; in the design of devices and systems by simulation using specialized software products; in the creation of knowledge bases of expert systems. |
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Intendend use/applicability |
Modules: Research Scientific Training, Final Academic Assessment |
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Content: |
Theory of Simulation and Scientific Experiment Classification, types and objectives of the experiment, singlefactor and multifactorial experiment, experimental technique. Measurement methods, absolute and relative errors, single and multiple measurements. Mathematical statistics, tasks and main sections of mathematical statistics, general and sample population, sampling, sample representativeness, sample parameterization, application of built-in Excel tools for statistical data processing. Investigation of experimental data on the reliability and reproducibility of the experimental results. Wavelet Theory Optimization problems, linear programming, objective function, constraints in the form of equations and inequalities, least squares method. A trend line, approximating functions, accuracy of approximation, the coefficients of determination. Application of the wavelet theory. Application of Microprocessors in Electric Power Systems Philosophy of microprocessor technology. Bus microprocessor systems and cycles of exchange. Backbone device features. Addressing operands. Command system of the processor. Processor core and microcontroller memory. Organization of communication of the microcontroller with the environment and time. Auxiliary hardware of the microcontroller. Microprocessor-Based Automatic Control Systems AVR microcontrollers. Introduction to Arduino. Download and run the sample sketch in IDE Arduino. Arduino. Creating one’s own sketch. Use of mathematical operators. Serial interface. Arduino. Digital and analog input. Receiving input data from sensors. Arduino. Physical and visual data output. Arduino. The use of PWM signals generated by Arduino. Arduino. Remote control of external devices. Arduino. Realtime clock usage. Arduino. Using the display. Arduino. I2C and SPI data interfaces. Arduino. Communication via wireless interfaces. Automated ZigBee technology. The system of commands used in ZigBee technology. Digital Automation and Control Systems in Electric Power Engineering PIC series of microcontroller hardware. Special functions and command system of PIC series microcontrollers. Features of development of digital devices based on microcontrollers. Software development for PIC microcontrollers. Architecture and processors of personal computers. Development of simple digital devices. Devices that are part of a personal computer. Information Technologies in Electric Power Engineering Structure and content of the course. Signal Coordination Systems. Asynchronous input/output of digital signals: line, port. Synchronous input/output of digital arrays. Organization of communication of data analysis systems with the external environment and time. Measurement errors. Regulation of errors and correction of measurement results. Modeling of intelligent systems. Equal and unequal measurements. Single measurements. Indirect measurements. Logical-linguistic description of systems. Normalization of metrological properties of measuring tools. Additive and multiplicative component of the measuring tool error. Connection layout of measuring devices. The calculation of the error of the measuring system. Network Technologies Local networks and their topology. Place and role of local networks. Media of information communication. Wireless communication channels. Optic cable. The levels of network architecture. OSI reference model. The apparatus of local networks. Protection of information in local networks. Standard local networks. Ethernet and Fast Ethernet Ethernet/fast ethernet network algorithms. Standard Ethernet and fast Ethernet segments. Logical network structuring using bridges and switches. Principles of network interconnection based on network layer protocols. The main characteristics of routers and hubs. Domains. Global network. Monitoring and analysis of local networks. Main stages of professional development of personality and their characteristics. Elements of Artificial Intelligence in Technical Systems Philosophical aspects of AIS problem. History of the development of AIS. Analog I / o. Issues of AIS Simulation. Expert system as a kind of AIS. Coordination of the signals. The methodology for developing expert systems. Models of knowledge representation. Models of decisions output and communication in AIS. Fuzzy sets. Fuzzy relations. Fuzzy and linguistic variables. Fuzzy statements and fuzzy system models. Logical-linguistic description of systems. Artificial neural network. System Simulation Classification of system models. Methods of simulation of electric power systems. Methods of description of electric power equipment as a control object. Structural and mathematical models. Simulation modeling. Intelligent Measuring Instruments Structure and content of the course of Intelligent Measuring Instruments. Initial provisions and review of the state of research on the intellectualization of measurements and measuring instruments. Application of nanostructures in the measuring instruments. Artificial neural network. Modern directions of development of neural network technologies. Application of neural networks to solve practical problems. Methods of knowledge formalization. Model of measuring knowledge representation. Features of the hardware of intelligent measuring instruments. Features of the software of intelligent systems. Systems of Computer Mathematics Introduction. Evolution of computer mathematics systems. System of computer mathematics MathCAD. Organization of calculations. Data types. System of computer mathematics MATLAB. Visual Simulation Systems Programming in MATLAB. Functions of applied and numerical mathematics. Classes of computational objects. Digital signal processing. Signal Processing Toolbox. Procedures of spectral (frequency) and statistical analysis of processes. Automated Data Collection Systems Filters design. Investigation of linear stationary systems. Modeling of nonlinear systems (Simulink package). Matlab expansion packs. Interface design. LabVIEW modeling and data acquisition system. |
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Examination Form, module mark: |
Theory of Simulation and Scientific Experiment - written examination Wavelet Theory - Computer-based testing Application of Microprocessors in Electric Power Systems - Computer-based testing Microprocessor-Based Automatic Control Systems - Computer-based testing Digital Automation and Control Systems in Electric Power Engineering - written control examination Information Technologies in Electric Power Engineering - Computer-based testing Network Technologies - written control examination Elements of Artificial Intelligence in Technical Systems - Computer-based testing System Simulation - Computer-based testing Intelligent Measuring Instruments - written examination Systems of Computer Mathematics - Computer-based testing Visual Simulation Systems - Computer-based testing Automated Data Collection Systems - Computer-based testing Module mark: written examination Elective Subject |
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Technical/Multimedia Facilities: |
Multimedia system. Laboratories of Computer Mathematics and Electronic Simulation, Simulation of Power Devices and Systems, Digital Devices and Microprocessors and Electrical Power Engineering |
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Study Materials: |
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Date of last amendment |
20.01.2023 |