关键词: 风电机组, 齿轮箱, 代价敏感支持向量机, 增量学习, 故障诊断

Abstract: Aiming at lack of fault samples and plenty of normal samples in the running process of wind turbine gearbox, a novel fault diagnosis of wind turbine gearbox method based on Incremental Cost-sensitive Support Vector Machine（ICSVM） is proposed. Due to lack of the fault samples, ICSVM fault diagnosis model which aims to minimize misclassification costs is built. In the training period of incremental cost-sensitive support vector machine, ICSVM using KKT conditions is trained by incremental samples and initial samples. Experimental results show that the proposed method reduces average misclassification costs and training time, and increases recognition rate of gearbox fault.

Key words: wind turbine, gearbox, cost-sensitive support vector machine, incremental learning, fault diagnosis