基于小波包和Hilbert包络分析的隧道掘进机主轴承故障诊断方法研究

Research on fault diagnosis method of main bearing of tunnel boring machine based on wavelet packet and Hilbert envelope analysis

隧道掘进机施工中,主轴承故障对掘进施工影响严重。该文提取主轴承振动信号,采用小波包和Hilbert包络分析相结合的方法,对信号进行分析,获得轴承故障信息。利用小波包变换滤波方法提取轴承高频固有共振频带信号,对所提取的信号进行重构,滤除其中的干扰成分;对重构信号进行Hilbert包络谱解调,去除高频固有共振成分,获得轴承故障信息。通过对振动传感器采集的轴承径向振动信号分析,有效地获得了轴承故障特征,验证了理论方法的正确性。

In the construction of tunnel boring machine,the main bearing fault has a serious influence on the tunneling construction. In this paper,vibration signals of main bearings are extracted. Wavelet packet and Hilbert envelope analysis are used to analyze the signals,and the fault information of bearings is obtained. The wavelet packet transform filtering method is used to extract the high-frequency natural resonance frequency band signal of the bearing,the extracted signal is reconstructed and the interference components are filtered out. The reconstructed signal is demodulated by Hilbert envelope spectrum,and the high frequency inherent resonance component is removed to obtain the bearing fault information.By analyzing the radial vibration signals of the bearings collected by the vibration sensors,the fault characteristics of the bearings are effectively obtained,and the correctness of the theoretical methods is verified.