关键词: 风力发电机, 故障诊断, 小波包分解, D-S证据理论, 支持向量机

Abstract: Aiming at the mechanical and electrical faults of wind turbine generator, this paper presents a D-S fusion model based on electrical feature vector and vibrational feature vector. We construct two parameter-optimized support vector machines, as two evidences to predict the final fault pattern. Compared with the traditional fault diagnosis of generator for mechanical fault and electrical fault with vibration sensor and current sensor to distinguish different faults by spectrum characteristics, evidence fusion method can make current signal used for mechanical fault diagnosis, also vibration signal can be used for electric fault. Through a large number of experimental data analysis, fusion model compared with only a single signal structure has higher classification accuracy.

Key words: wind power generator, fault diagnosis, wavelet packet, D-S evidence theory, SVM