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A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures

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  • Guo, Yongjin
  • Zhong, Mingjun
  • Gao, Chao
  • Wang, Hongdong
  • Liang, Xiaofeng
  • Yi, Hong

Abstract

The dynamic and dependant behaviors are typical characteristics of modern complex systems, whose reliability is often improved through the design of multichannel parallel structures. The existence of common cause failures (CCFs) has a significant impact on system reliability. A reliability analysis model is proposed for dynamic systems with CCFs based on discrete-time Bayesian networks (DTBNs). The system operating time is dispersed into several time intervals, and the component failures are divided into independent and CCF states. Dynamic systems with cold and warm spare parts are examined to determine the modelling methodology and conditional probability tables (CPTs) of Bayesian network (BN) nodes. The reliability calculation is realised through the Bayesian inference mechanism. The model is applied to the CCF analysis and fault diagnosis of a digital safety-level distributed control system (DCS) of nuclear power plants (NPPs) to prove the effectiveness and feasibility of the method.

Suggested Citation

  • Guo, Yongjin & Zhong, Mingjun & Gao, Chao & Wang, Hongdong & Liang, Xiaofeng & Yi, Hong, 2021. "A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021005366
    DOI: 10.1016/j.ress.2021.108028
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    References listed on IDEAS

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    Cited by:

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    4. Bao, Han & Zhang, Hongbin & Shorthill, Tate & Chen, Edward & Lawrence, Svetlana, 2023. "Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
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    7. Gao, Shan, 2023. "Reliability analysis and optimization for a redundant system with dependent failures and variable repair rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 637-659.
    8. Martínez-Galán Fernández, Pablo & Guillén López, Antonio J. & Márquez, Adolfo Crespo & Gomez Fernández, Juan Fco. & Marcos, Jose Antonio, 2022. "Dynamic Risk Assessment for CBM-based adaptation of maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    9. Guo, Yongjin & Wang, Hongdong & Guo, Yu & Zhong, Mingjun & Li, Qing & Gao, Chao, 2022. "System operational reliability evaluation based on dynamic Bayesian network and XGBoost," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
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    11. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).

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