4.7 Article

A developed failure mode and effect analysis for floating offshore wind turbine support structures

期刊

RENEWABLE ENERGY
卷 164, 期 -, 页码 133-145

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2020.09.033

关键词

FMEA; Failure analysis; Risk analysis; Support structure; Floating offshore wind turbine

资金

  1. European Regional Development Fund through the Interreg Atlantic Area Programme [EAPA 344/2016]
  2. China Scholarship Council (CSC) [201806070048]
  3. Portuguese Foundation for Science and Technology (Fundacao para a Ciencia e Tecnologia - FCT) [UIDB/UIDP/00134/2020]

向作者/读者索取更多资源

This study extends the conventional failure mode and effect analysis methodology by introducing weights for severity, occurrence, and detection to analyze failures in the support structure of a floating offshore wind turbine. Recommendations for corrections and preventive actions are suggested based on the analysis. The proposed technique is validated through a comparison study, showing that it is more in line with practical use and offers flexibility.
This paper extends the conventional failure mode and effect analysis methodology by introducing weights of its indices that are severity, occurrence, and detection as a basis to analyze the failures of the support structure of a generic floating offshore wind turbine. Critical failure causes, failure modes, as well as systems of the support structure of the floating offshore wind turbine are ascertained. Moreover, based on the analysis, recommendations on corrections and preventive actions are suggested aiming at ensuring the safe and economic operations of the support structure. The validation of the proposed technique is finalized by a comparison study between the results of conventional failure mode and effect analysis methodology and that of the proposed method. The comparison indicates that the proposed technique is more in line with practice and flexible for use and has the merit in removing the limitations of conventional failure mode and effect analysis methodology that different failure causes generate the same risk priority number. (C) 2020 Elsevier Ltd. All rights reserved.

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