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

Hao Xu, Jinqian Zeng, Lingzhi Xi, Hui Huang, Qiang Zhang, Dingding Yang, Rui Wang, Chengyuan Zhang, Zhenming Li and Xinjiao Tian ()
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Hao Xu: Powerchina Huadong Engineering 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
Hui Huang: Powerchina Huadong Engineering Corporation Limited, Hangzhou 311122, China
Qiang Zhang: Powerchina Huadong Engineering 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

Energies, 2025, vol. 18, issue 18, 1-26

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.

Keywords: offshore wind power; pile pitching and pulling; fault tree analysis; fuzzy Bayesian network; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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