基于支持向量机的风电机组变桨系统故障诊断

张真真; 吴立东; 陈晓敏; 徐志轩; 曹善桥

doi:10.16513/j.2096-2185.DE.2106512

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分布式能源 ›› 2021, Vol. 6 ›› Issue (3) : 70-75. DOI: 10.16513/j.2096-2185.DE.2106512

应用技术

基于支持向量机的风电机组变桨系统故障诊断

作者信息 +

Fault Diagnosis of Wind Turbine Pitch System Based on Support Vector Machine

Author information +

文章历史 +

摘要

风电机组变桨系统是风电机组发生故障最频繁的部件之一，对其故障类型的精确诊断能够提高风电机组维护计划的效率。针对异步电机和行星齿轮箱的各种故障类型，提出了一项以风电机组三相电流数据为基础的多分量故障诊断方法。该方法通过深度自动编码器从三相电流数据中提取特征向量，并采用支持向量机进行故障分类。上述方法以风电机组变桨驱动器为例进行验证，实验结果表明在变负载和变转速环境下，上述方法能够实现对风电机组变桨系统故障类型的准确识别和诊断。

Abstract

The rotor system of wind turbine is the most fragile parts of wind turbine, and accurate diagnosis of its fault categories can improve the effectiveness of wind turbine maintenance. A multi-component fault diagnosis method based on the three-phase currents data of wind turbine was proposed for various fault categories of induction motor and planetary gearbox. The method extracted feature vectors from three-phase currents data by deep auto-encoder and used support vector machine for fault classification. The above method was verified by an example of a rotor driver of wind turbine. The experimental results show that the method can accurately identify and diagnose the fault categories of rotor driver under variable load and variable speed environment.

导出引用

张真真, 吴立东, 陈晓敏, 等. 基于支持向量机的风电机组变桨系统故障诊断[J]. 分布式能源. 2021, 6(3): 70-75 https://doi.org/10.16513/j.2096-2185.DE.2106512

Zhenzhen ZHANG, Lidong WU, Xiaomin CHEN, et al. Fault Diagnosis of Wind Turbine Pitch System Based on Support Vector Machine[J]. Distributed Energy Resources. 2021, 6(3): 70-75 https://doi.org/10.16513/j.2096-2185.DE.2106512

中图分类号： TM83

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