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 bearings is a very important part of coal mining machinery, but also one of the most prone to failure components. Fault diagnosis of coal mine rolling bearings is a very hot direction. A fault feature extraction method combining independent quantitative analysis and wavelet packet energy spectrum is proposed. The fault feature of rolling bearing is extracted by this method. The experimental results show that the method of combining the independent quantitative analysis and the wavelet packet energy spectrum to extract the fault of the rolling bearing is obviously better than the wavelet packet energy spectrum alone. This fault feature extraction method also applies to other equipment fault diagnosis.