Nuclear Engineering and Technology

  • 제55권5호
  • /
  • Pages.1901-1910
  • /
  • 2023
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Reliability analysis of nuclear safety-class DCS based on T-S fuzzy fault tree and Bayesian network

  • Xu Zhang (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • Zhiguang Deng (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • Yifan Jian (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • Qichang Huang (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • Hao Peng (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • Quan Ma (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China)
  • 투고 : 2022.05.31
  • 심사 : 2023.01.30
  • 발행 : 2023.05.25
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초록

The safety-class (1E) digital control system (DCS) of nuclear power plant characterized structural multiple redundancies, therefore, it is important to quantitatively evaluate the reliability of DCS in different degree of backup loss. In this paper, a reliability evaluation model based on T-S fuzzy fault tree (FT) is proposed for 1E DCS of nuclear power plant, in which the connection relationship between components is described by T-S fuzzy gates. Specifically, an output rejection control system is chosen as an example, based on the T-S fuzzy FT model, the key indicators such as probabilistic importance are calculated, and for a further discussion, the T-S fuzzy FT model is transformed into Bayesian Network(BN) equivalently, and the fault diagnosis based on probabilistic analysis is accomplished. Combined with the analysis of actual objects, the effectiveness of proposed method is proved.

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과제정보

The project was funded by Sichuan Provincial Youth Science and Technology Fund (2020JDJQ0068).

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