Weight-embedded fuzzy FMEA framework for enhanced risk prioritization of offshore wind turbines

Chen, Erhong and Luo, Xiaofang and Ma, Xiandong and Bai, Xu and Luo, Jiaxuan (2025) Weight-embedded fuzzy FMEA framework for enhanced risk prioritization of offshore wind turbines. Ocean Engineering, 341: 122649. ISSN 0029-8018

Text (OE paper)
OE_paper.pdf - Accepted Version
Available under License Creative Commons Attribution.
Download (1MB)

Abstract

With the rapid expansion of offshore wind power, wind turbines are increasingly exposed to complex environmental conditions and operational uncertainties. To ensure long-term operational reliability, this paper proposes an enhanced Failure Mode and Effect Analysis (FMEA) framework integrating Fuzzy Analytic Hierarchy Process (FAHP) with a Mamdani-based fuzzy inference system for risk assessment of offshore wind turbines. The proposed framework aims to simultaneously address the key shortcomings of FMEA in risk assessment of offshore wind turbine, particularly the neglect of expert evaluation fuzziness, inefficient fuzzy rule generation, and inadequate risk classification. The main contributions of this method are as follows. First, FAHP-derived consensus weights for risk factors (Severity, Occurrence, Detection) are embedded into fuzzy rules. Second, risk level distribution matrices automate rule generation, ultimately improving efficiency by a factor of 40 compared to traditional multi-expert integration. Third, risk prioritization (risk value) and classification are conducted through defuzzification, enabling the implementation of differentiated operation and maintenance (O&M) strategies. The framework is validated using operational data from an 80-turbine offshore wind farm in China, where critical failure modes (e.g., generator overheating, r = 0.786) were identified. Comparative analysis with Weighted FMEA confirmed the framework's effectiveness in preserving fuzzy information and optimizing risk ranking.