基于谐波小波和Hilbert的滚动轴承故障诊断方法

Fault diagnosis based on harmonic wavelet and Hilbert in rolling bearing

主轴滚动轴承是数控机床的重要部件,它的运行状态往往直接影响整套机械设备的性能。为了提高主轴滚动轴承的故障诊断可靠性,针对数控机床主轴轴承振动信号非平稳的特点,利用谐波小波滤波的方法对现场采集的振动信号进行滤波,并提出对滤波后的信号进行Hilbert包络分析,从而提取出故障激发的共振信号。实例验证表明,谐波小波具有良好的滤波效果,Hilbert包络分析能有效地提取滤波后信号的故障特征,此方法提高了数控机床主轴滚动轴承故障诊断的准确性。

Spindle rolling bearing is one of the most important components in spindle unit. The running state often affects the per- formance of the CNC machine tool spindle transmission system directly. In order to improve the reliability of fault diagnosis of spindle rolling beating, the method of harmonic wavelet filtering is used to diagnose the vibration signals collected at the scene ac- cording to the characteristics of non-stationary of CNC machine tool spindle rolling bearing＇ s vibration signals. And the Hilbert envelopment analysis of the filtered signal is proposed to extract the fauh characteristic of rolling bearings. The example shows that, the harmonic wavelet fiheting method has a good filtering effect, Hilbert envelopment analysis can extract the fault feature of the filtered signals effectively and the method improve the accuracy of fault diagnosis of CNC machine tool spindle rolling beating.