摘要
滚动轴承是煤矿机械中很重要的零部件,也是最容易发生故障的零部件之一。对煤矿机械滚动轴承的故障诊断研究是一个很热的方向。提出了一种将独立量分析和小波包能量谱相结合的故障特征提取方法,并采用此方法对滚动轴承进行了故障特征提取。实验结果说明采用独立量分析和小波包能量谱相结合的方法对滚动轴承故障进行提取的效果要明显优于单独使用小波包能量谱的方法。这种故障特征提取方法对其他设备的故障诊断也都适用。
Rolling bearing is a very important parts and components of coal mine machinery, and it is also one of the easiest parts which will cause problem. For a long time, research on fault diagnosis of rolling bearings is a hot direction. In this paper a kind of fault feature extraction method based on independent component analysis and wavelet packet energy spectrum analysis is proposed. And adopts this method carried out fault feature extraction for the rolling bearing. The experiment results shows that using the combination method of independent component analysis and wavelet packet energy spectrum analysis for rolling bearing fault extraction significantly superior to the effect of using only wavelet packet energy spectrum analysis method. This kind of fault feature extraction methods for faultdiagnosis of other instruments are also applicable.
出处
《煤矿机械》
北大核心
2013年第10期258-260,共3页
Coal Mine Machinery
关键词
滚动轴承
独立量分析
小
波包能量谱
故障诊断
rolling bearing
independent component analysis
wavelet packet energy spectrumanalysis
fault diagnosis
