Mechanics & Industry
Volume 19, Number 2, 2018
|Number of page(s)||9|
|Published online||03 September 2018|
Synthesis of the equipment health management system of the turbine units' of thermal power stations
Kazakh National Technical University named after Satpayev K.I.,
2 Taraz State University after M. Kh Dulati, Taraz, Kazakhstan
* e-mail: email@example.com
Accepted: 7 December 2017
The aim of the research is the development of technical diagnostics subsystem with the possibility of its further integration into the automated system of equipment health management, which will improve the efficiency of data ware, hardware and software. Synthesis of intellectual diagnostic models was produced a by using the Matlab graphical agents. At the same time, there were synthesized models of three types: fuzzy, neural-network and model built by planning the full factorial experimental method. Was proposed the concept of the three-stage procedure of the diagnosis of the thermal power station's turbine unit, instead of the creation of diagnosis mathematical models and failure models of objects, immediately begin to develop an algorithm of diagnosis using advanced intelligent technologies. The technique of creating a sub-line diagnostics status of the turbine unit, which includes three main stages: identification of diagnostic features based on expert method; the synthesis of diagnostic model of the facility technical condition; research models on the stability, sensitivity and uniqueness, was proposed. The main diagnostic features of assessing the state of turbine equipment, which, in accordance with the concept developed, allow forming a matrix of planning a full factorial experiment. The proposed techniques and concepts were subjected to experimental verification. The intellectual diagnostic model of turbine unit equipment health was proposed, synthesized and investigated. It was found that the best model is the model, built using neuro-fuzzy algorithms. The simulation was provided for neuro-fuzzy algorithms and confirmed their effectiveness and compliance with the laws of the physical functioning of the HPC. The results of this research have been used in the development of Almaty CHP-2 turbine equipment health management subsystems, allow the further development of the theoretical foundations of intellectual systems, and demonstrate the possibility of using modern concepts to solve important technical problems. Subsystem of operative diagnosis and the following software implementation in a complex of automated technological process of thermal power control system allows one to make an early diagnosis of the equipment health. This significantly reduces the maintenance costs, improves reliability and security, as well as the effectiveness of the control system. In this regard, the results of this study provide further development of the theoretical foundations of the intellectual systems and demonstrate the possibility of modern concepts usage to determinate the important technical problems.
Key words: Equipment health management / a full factorial experiment / expert systems / fuzzy systems / intellectual technology / neural-network models / neuro fuzzy algorithms / technical diagnostics / thermal station / turbine unit
© AFM, EDP Sciences 2018
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