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Risk Analysis of Pile Pitching and Pulling on Offshore Wind Power Jack-Up Platforms Based on a Fault Tree and Fuzzy Bayesian Network

Author

Listed:
  • Hao Xu

    (Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China
    Powerchina Zhejiang Huadong Engineering Consulting Corporation Limited, Hangzhou 311122, China)

  • Jinqian Zeng

    (Institute of Accident Prevention Science, Zhejiang University of Technology, Hangzhou 310014, China)

  • Lingzhi Xi

    (Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China
    Powerchina Zhejiang Huadong Engineering Consulting Corporation Limited, Hangzhou 311122, China)

  • Hui Huang

    (Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China
    Powerchina Zhejiang Huadong Engineering Consulting Corporation Limited, Hangzhou 311122, China)

  • Qiang Zhang

    (Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China
    Powerchina Zhejiang Huadong Engineering Consulting Corporation Limited, Hangzhou 311122, China)

  • Dingding Yang

    (School of Petrochemical Engineering & Environment, Zhejiang Ocean University, No. 1, Haida South Road, Zhoushan 316022, China)

  • Rui Wang

    (Institute of Accident Prevention Science, Zhejiang University of Technology, Hangzhou 310014, China)

  • Chengyuan Zhang

    (Institute of Accident Prevention Science, Zhejiang University of Technology, Hangzhou 310014, China)

  • Zhenming Li

    (Institute of Accident Prevention Science, Zhejiang University of Technology, Hangzhou 310014, China)

  • Xinjiao Tian

    (Institute of Accident Prevention Science, Zhejiang University of Technology, Hangzhou 310014, China)

Abstract

Safety accidents during pile pitching and pulling operations on offshore wind power jack-up platforms occur frequently, yet research into their underlying causes is insufficient. This study delved into the causes of accidents related to pile pitching and pulling and put forward corresponding risk prevention and control measures by integrating the Fault Tree Analysis (FTA) and Fuzzy Bayesian Network (FBN) in consideration of the high-risk characteristics of these operations. Firstly, this study expounded the causal relationship of risk factors in the pile pitching and pulling operations on offshore wind power jack-up platforms via FTA. Secondly, the events in the FTA model were mapped to the FBN nodes. The prior probabilities of each node were determined through expert evaluation, and a Fuzzy Bayesian Network model was constructed. Finally, risk diagnosis and prediction were carried out through probability updating and a sensitivity analysis. The results indicate that environmental risks, including water depth, strong winds, heavy waves, and unknown subsea geology, exert the most significant influence. Equipment malfunctions and management problems are the key causes of accidents. A sensitivity analysis reveals that failures in the pile driving system and underwater monitoring system are highly sensitive triggers for the top-level event. Improvement measures are proposed to mitigate risks and enhance project safety.

Suggested Citation

  • Hao Xu & Jinqian Zeng & Lingzhi Xi & Hui Huang & Qiang Zhang & Dingding Yang & Rui Wang & Chengyuan Zhang & Zhenming Li & Xinjiao Tian, 2025. "Risk Analysis of Pile Pitching and Pulling on Offshore Wind Power Jack-Up Platforms Based on a Fault Tree and Fuzzy Bayesian Network," Energies, MDPI, vol. 18(18), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:18:p:4954-:d:1751925
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    References listed on IDEAS

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    1. Montani, S. & Portinale, L. & Bobbio, A. & Codetta-Raiteri, D., 2008. "Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 922-932.
    2. Gan, Langxiong & Gao, Ziyi & Zhang, Xiyu & Xu, Yi & Liu, Ryan Wen & Xie, Cheng & Shu, Yaqing, 2025. "Graph neural networks enabled accident causation prediction for maritime vessel traffic," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
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