MATEC Web Conf.
Volume 161, 201813th International Scientific-Technical Conference on Electromechanics and Robotics “Zavalishin’s Readings” - 2018
|Number of page(s)||4|
|Section||Electromechanics and Electric Power Engineering|
|Published online||18 April 2018|
Intellectual decision-making system in the context of potentially dangerous nuclear power facilities
Voronezh State Technical University, 394026, Voronezh, Russia
2 Novovoronezh Nuclear Power Plant, 396072, Novovoronezh, Russia
* Corresponding author: firstname.lastname@example.org
The article deals with intelligent operation decision support system under condition of potentially hazardous nuclear facilities. The proposed system is referred to the class of advising systems and does not make final decisions in case of deviations of parameters to be analyzed, but generates general ways to solve an encountered problem and issues a set of recommendations for the plant personnel. In the article a fuzzy logic tool is used as mathematic tool. Lessons learnt from operation of nuclear facilities demonstrate that existing critical components (parts, areas, welding joints) are subject to increased failure under conditions of high operational loads, including beyond design loads and negative environmental impact. Usually in that situation there is probability of equipment integrity failure, when the unit is at power, with severe defect downing. For instance, the coolant leak and potential development of initial penetration defect to critical dimensions. In other words, in fact, the final observable result is always one – formation and development of operational crack which jeopardizes design integrity of the component and, accordingly, seriously compromises the nuclear power unit operation. The proposed situational model is linked with real knowledge data base where generated situational pairs are stored. The expert system is used for knowledge data base formation. Actually the proposed system consists of two independent fuzzy systems. From mathematical tool point of view, the advantage of such systems combination is lack of defuzzification unit in the first system and fuzzification unit in the second one.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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