A Fuzzy-FMEA Risk Assessment Approach for Offshore Wind Turbines

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 windfarms: (i) the failure data gathered from SCADA system is often missing or...

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Bibliographic Details
Main Authors: M. Shafiee, F. Dinmohammadi
Format: Article
Language:English
Published: The Prognostics and Health Management Society 2013-01-01
Series:International Journal of Prognostics and Health Management
Subjects:
Online Access:http://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2013/ijphm_13_013.pdf
Description
Summary: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 windfarms: (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 onexperts’ 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 riskfactors 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.
ISSN:2153-2648