Abstract
Failure Mode and Effects Analysis (FMEA) has been extensively used by wind turbine assembly manufacturers for risk and reliability analysis. However, several limitations are associated with its implementation in offshore wind farms: (i) the failure data gathered from SCADA system is often missing or unreliable, and hence, the assessment information of the three risk factors (i.e., severity, occurrence, and fault detection) are mainly based on experts’ knowledge; (ii) it is rather difficult for experts to precisely evaluate the risk factors; (iii) the relative importance among the risk factors is not taken into consideration, and hence, the results may not necessarily represent the true risk priorities; and etc. To overcome these drawbacks and improve the effectiveness of the traditional FMEA, we develop a fuzzy-FMEA approach for risk and failure mode analysis in offshore wind turbine systems. The information obtained from the experts is expressed using fuzzy linguistics terms, and a grey theory analysis is proposed to incorporate the relative importance of the risk factors into the determination of risk priority of failure modes. The proposed approach is applied to an offshore wind turbine system with sixteen mechanical, electrical and auxiliary assemblies, and the results are compared with the traditional FMEA.
Highlights
Offshore wind energy has experienced an extensive and worldwide growth during the past several years
Even though Failure Mode and Effects Analysis (FMEA) is probably the most popular tool for reliability and failure mode analysis in wind turbine systems, several limitations are associated with its implementation in offshore wind farms: (i) The failure data gathered from inspectors, vibration sensors, and the SCADA system is often missing or unreliable
To overcome the above drawbacks and improve the effectiveness of the traditional FMEA methodology, we develop a fuzzy-FMEA approach to determine the effects of failure on offshore wind turbine systems
Summary
Offshore wind energy has experienced an extensive and worldwide growth during the past several years. Even though FMEA is probably the most popular tool for reliability and failure mode analysis in wind turbine systems, several limitations are associated with its implementation in offshore wind farms:. The results of the traditional FMEA methodology may not necessarily represent the true risk priorities in offshore wind turbine systems, and this can entail a waste of resources and time. To overcome the above drawbacks and improve the effectiveness of the traditional FMEA methodology, we develop a fuzzy-FMEA approach to determine the effects of failure on offshore wind turbine systems. This paper is the first attempt to make the traditional FMEA methodology more applicable for offshore wind turbine systems, especially when the failure data is unavailable or unreliable.
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