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<p>Wind energy has been emerged as a crucial pillar of the global transition toward renewable energy systems. Nevertheless, wind turbines are susceptible to some complex and premature failures that compromise system reliability, increase maintenance costs, and lead to energy losses. Effective reliability assessment of these systems entails advanced methods capable of addressing uncertainty and ambiguity in failure analysis. Classical Failure Mode and Effects Analysis (FMEA), despite being widely adopted, is limited by its incapability to reflect expert uncertainty as well as its dependence on crisp numerical values. It may lead to non-unique failure priority rankings and lacks flexibility in dynamic or complex systems. In order to overcome these drawbacks, we have introduced a fuzzy logic-based FMEA framework that incorporates fuzzy variables, linguistic terms, and a fuzzy inference mechanism to model imprecise and subjective judgments within the mathematical foundation of fuzzy set theory. This allows for a more realistic depiction of vagueness and subjective reasoning in failure analysis.The developed Fuzzy FMEA framework was applied to wind turbine and has demonstrated its ability to produce consistent and discriminative prioritization of critical failures. It offers a scalable, interpretable, and theory-grounded approach to failure mode analysis as well as informed decision-making in complex engineering environments.</p>

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A fuzzy logic-based framework for failure mode and effects analysis in wind turbines

  • 期刊论文

  • 发表日期：

    2026年6月23日

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  • Abdelkader Abdelmoumene,
  • Abdelbasset Krama

摘要

Wind energy has been emerged as a crucial pillar of the global transition toward renewable energy systems. Nevertheless, wind turbines are susceptible to some complex and premature failures that compromise system reliability, increase maintenance costs, and lead to energy losses. Effective reliability assessment of these systems entails advanced methods capable of addressing uncertainty and ambiguity in failure analysis. Classical Failure Mode and Effects Analysis (FMEA), despite being widely adopted, is limited by its incapability to reflect expert uncertainty as well as its dependence on crisp numerical values. It may lead to non-unique failure priority rankings and lacks flexibility in dynamic or complex systems. In order to overcome these drawbacks, we have introduced a fuzzy logic-based FMEA framework that incorporates fuzzy variables, linguistic terms, and a fuzzy inference mechanism to model imprecise and subjective judgments within the mathematical foundation of fuzzy set theory. This allows for a more realistic depiction of vagueness and subjective reasoning in failure analysis.The developed Fuzzy FMEA framework was applied to wind turbine and has demonstrated its ability to produce consistent and discriminative prioritization of critical failures. It offers a scalable, interpretable, and theory-grounded approach to failure mode analysis as well as informed decision-making in complex engineering environments.