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A new risk assessment method based on belief rule base and fault tree analysis

Author

Listed:
  • Hai-Long Zhu
  • Shan-Shan Liu
  • Yuan-Yuan Qu
  • Xiao-Xia Han
  • Wei He
  • You Cao

Abstract

Risk assessment methods are often used in complex industrial systems to avoid risks and reduce losses. The existing methods have not effectively solved the problems of lack of evaluation data and the interpretability of the entire evaluation process. This paper proposes a new risk assessment model based on the belief rule base (BRB) and Fault Tree Analysis (FTA). The FTA algorithm overcomes the difficulties of traditional BRB model in obtaining expert knowledge, clear indicators, and establishing logical relationships. This method establishes FTA rules based on the BRB model and expands the knowledge base through the FTA algorithm. A Bayesian network is applied as a conversion bridge between the FTA and BRB model. In addition, the model is optimized to reduce the uncertainty in the model. The method proposed is described by a case and its effectiveness is verified.

Suggested Citation

  • Hai-Long Zhu & Shan-Shan Liu & Yuan-Yuan Qu & Xiao-Xia Han & Wei He & You Cao, 2022. "A new risk assessment method based on belief rule base and fault tree analysis," Journal of Risk and Reliability, , vol. 236(3), pages 420-438, June.
    • Handle: RePEc:sae:risrel:v:236:y:2022:i:3:p:420-438
    DOI: 10.1177/1748006X211011457
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    References listed on IDEAS

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    1. Kjartan Bjørnsen & Anders Jensen & Terje Aven, 2020. "Using qualitative types of risk assessments in conjunction with FRAM to strengthen the resilience of systems," Journal of Risk Research, Taylor & Francis Journals, vol. 23(2), pages 153-166, February.
    2. Bani-Mustafa, Tasneem & Flage, Roger & Vasseur, Dominique & Zeng, Zhiguo & Zio, Enrico, 2020. "An extended method for evaluating assumptions deviations in quantitative risk assessment and its application to external flooding risk assessment of a nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    3. Feng, Zhichao & Zhou, Zhijie & Hu, Changhua & Ban, Xiaojun & Hu, Guanyu, 2020. "A safety assessment model based on belief rule base with new optimization method," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Langdalen, Henrik & Abrahamsen, Eirik Bjorheim & Abrahamsen, HÃ¥kon Bjorheim, 2020. "A New Framework To Idenitfy And Assess Hidden Assumptions In The Background Knowledge Of A Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    5. Kong, Guilan & Xu, Dong-Ling & Body, Richard & Yang, Jian-Bo & Mackway-Jones, Kevin & Carley, Simon, 2012. "A belief rule-based decision support system for clinical risk assessment of cardiac chest pain," European Journal of Operational Research, Elsevier, vol. 219(3), pages 564-573.
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