摘要
为了提高直驱风机稳定发电能力,提出一种新型电机轴承故障诊断方法。采用小波变换对轴承的滚动体、内圈和外圈振动信号进行分解,利用小波能谱熵和高阶统计量的双谱计算振动信号特征值,使用支持向量机根据特征值构造故障分类器,最后通过仿真验证所提故障诊断方法的有效性。
In order to improve the stability of direct - driven wind power generation capacity, a new method of motor bearing fault diagnosis is proposed. Wavelet transform is used to decompose the vibration signal of tbe ball, inner raceway and outer raceway of the bearing, and the wavelet energy spectrum entropy and the bispectrum of high order statistics are used to calculate the characteristic value of vibration signal. The fault classifier based on characteristic value is constructed by support vector machine, and finally the effectiveness of the proposed fault diagnosis method is verified by the simulation.
出处
《四川电力技术》
2016年第6期41-46,共6页
Sichuan Electric Power Technology
关键词
轴承
故障诊断
小波变换
能谱熵
高阶统计量
双谱分析
支持向量机
bearing
fault diagnosis
wavelet transform
energy spectrum entropy
high order statistics
bispectrum analysis
support vector machine
