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Failure Analysis of Floating Offshore Wind Turbines with Correlated Failures

Author

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  • Sun, Yu
  • Li, He
  • Sun, Liping
  • Guedes Soares, C.

Abstract

A novel failure mode and effect analysis schedule, namely correlated-Failure Mode and Effect Analysis (FMEA), is proposed to identify critical failures of floating offshore wind turbines with correlated failures. A failure correlation model based on Bayesian networks is first presented as a basis to model common cause failures of floating offshore wind turbines. A new model is then developed to compute the Risk Priority Numbers of failure items, including systems, components, failure modes, and failure causes of floating devices. Critical failures of the holistic devices at all levels are identified with the proposed model and failure data collected from real wind farms. The validation of the results is finalized by a comprehensive comparative analysis with what has been concluded by the existing models, which show that the proposed correlated-FMEA schedule is superior in dealing with correlated failures in the failure analysis of floating offshore wind turbines. Overall, the proposed correlated FMEA approach contributes to the reliability and availability of floating offshore wind turbines and the operation and maintenance of floating wind farms.

Suggested Citation

  • Sun, Yu & Li, He & Sun, Liping & Guedes Soares, C., 2023. "Failure Analysis of Floating Offshore Wind Turbines with Correlated Failures," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
  • Handle: RePEc:eee:reensy:v:238:y:2023:i:c:s095183202300399x
    DOI: 10.1016/j.ress.2023.109485
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    Cited by:

    1. Zhang, Ruixing & An, Liqiang & He, Lun & Yang, Xinmeng & Huang, Zenghao, 2024. "Reliability analysis and inverse optimization method for floating wind turbines driven by dual meta-models combining transient-steady responses," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Zhang, Pei & Zhang, Zhen-Ji & Gong, Da-Qing, 2024. "An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

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