Improved criticality analysis method of equipment failures in wind turbines

Abstract

High failure rate and maintenance cost of wind turbines are one of the key issues in wind energy. In view of this, reliability centred maintenance (RCM) has been introduced to distinctively treat equipment failures according to their criticality. Criticality analysis (CA) is a pivotal step of RCM, derived from the failure frequency and failure modes effects of equipment, which determines when and how to maintain the wind turbines. However, in traditional CA, failure data is roughly considered, e.g. failure frequency is categorised as different ranks instead of accurate numerical value. In addition, the method of calculating criticality by multiplying variables is sensitive to variable ranges and values, which is unable to distinctly distinguish the contributions of different variables. Aimed at these deficiencies, an improved CA method with expansibility is proposed to assess the criticality of equipment failures in wind turbines based on Euclidean distance of failure vectors. To assess disparities among criticality ranks from diverse CA methods, an inverse number based method is presented. Several existing CA methods and the proposed CA in this study are compared using the data of wind turbines in literature, and the results verify the effectiveness of the proposed method.