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Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers

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Listed:
  • Yan-Feng Li
  • Jinhua Mi
  • Yu Liu
  • Yuan-Jian Yang
  • Hong-Zhong Huang

Abstract

In the calculation of dynamic fault trees, the existing state space–based methods, such as Markov chain method, are basically global-state models, which make the solution procedure very complex. Bayesian networks have become a popular tool to build probability models and conduct inference for reliability design and analysis in various industry fields. The “state explosion†problem can be alleviated by Bayesian networks. Furthermore, to obtain sufficient failure data sets in real engineering systems is extremely difficult and thus causes the parametric uncertainty in failure data. To address these issues, a novel dynamic fault tree analysis method based on the continuous-time Bayesian networks under fuzzy numbers is proposed in this article. The probability distributions under fuzzy numbers for the output variable of dynamic logic gates are determined. The calculation of fuzzy failure probability of a system is presented. Finally, an example is given to demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    • Handle: RePEc:sae:risrel:v:229:y:2015:i:6:p:530-541
    DOI: 10.1177/1748006X15588446
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    References listed on IDEAS

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    1. Li, Xiang-Yu & Huang, Hong-Zhong & Li, Yan-Feng, 2018. "Reliability analysis of phased mission system with non-exponential and partially repairable components," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 119-127.
    2. Mi, Jinhua & Li, Yan-Feng & Peng, Weiwen & Huang, Hong-Zhong, 2018. "Reliability analysis of complex multi-state system with common cause failure based on evidential networks," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 71-81.
    3. Zhang, Xiaoqiang & Gao, Huiying & Huang, Hong-Zhong & Li, Yan-Feng & Mi, Jinhua, 2018. "Dynamic reliability modeling for system analysis under complex load," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 345-351.
    4. Li, Xiang-Yu & Li, Yan-Feng & Huang, Hong-Zhong & Zio, Enrico, 2018. "Reliability assessment of phased-mission systems under random shocks," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 352-361.

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