Wind turbine blade health state assessment based on fuzzy evaluation

Abstract Due to the health state of wind turbine blade being affected by many factors and the mechanism being unclear, a fuzzy evaluation method using SCADA information is proposed. Firstly, the index structure of blade health state assessment is determined by correlation analysis of SCADA data. Secondly, entropy weight is used to allocate weights to all levels of parameters, and then the index data degradation function is optimized by the 3σ criterion. Thirdly, the ridge distribution function is utilized to establish the membership function of the health indexs. Finally, a mathematical model is created for the fuzzy comprehensive assessment of the blade health status. The described techniques is employed to assess the blade health state in the Qingdao wind farm. The “healthy” and “dangerous” states of the blade can be distinguished. The assessment result aligns with reality, verifying that the method in this paper is applicable to the blade health state assessment of wind farms.