Models and methods of improving the efficiency and safety of the operation of thermal power equipment – BOOKS OF THE NATIONAL ACADEMY OF SCIENCES OF UKRAINE

The monograph examines modern problems of increasing the efficiency and safety of the operation of thermal power equipment and ways to solve them. The available methods and systems for diagnosing complex thermal power facilities have been analysed and systematised. The features and parameters of diagnosing elements of complex thermal power facilities are presented, the general requirements for diagnostic systems are substantiated. Mathematical models of the investigated fields are developed, models and characteristics of the input signals of the measuring modules of the proposed information-measuring system of diagnostics using current and retrospective information are described. Methods of forecasting abnormal states of complex thermal power objects using machine learning algorithms with LSTM architectures have been developed. A system for monitoring and controlling the process of fuel combustion in small and medium power boilers is proposed, which is based on the use of an oxygen sensor and frequency-regulated blowing fans. A method of measuring the coefficient of excess air taking into account the current volume concentration of oxygen in the air is proposed. Modern methods and algorithms for solving linear and non-linear inverse heat conduction problems of various nature are considered. A technique for obtaining the numerical solution of the main classes of inverse problems of heat conduction has been developed, which makes it possible to reduce the total number of calculations required to find the global minimum of the quadratic functional used in the formulation of most inverse problems.

For researchers, engineers, as well as teachers, graduate students and students of higher educational institutions deal with the problems of increasing the efficiency and safety of the operation of energy equipment.

Keywords:

thermal power equipment, boiler, technical condition, fuel combustion, efficiency, diagnostics, monitoring, control, neural networks, machine learning, algorithms, models, inverse problem, heat exchange

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