基于时域多普勒校正和EEMD的列车轴承道旁声音监测故障诊断方法研究  

Wayside acoustic fault diagnosis for locomotive bearings based on Doppler effect correction and EEMD method in time domain

作　　者：刘方[1] 沈长青[1] 何清波[1] 胡飞[1] 张翱[1] 孔凡让[1] 

机构地区：[1]中国科学技术大学精密机械与精密仪器系,合肥230027

出　　处：《振动与冲击》2013年第24期104-109,共6页Journal of Vibration and Shock

基　　金：国家自然科学基金资助项目(51075379)

摘　　要：提出一种列车轴承的道旁声音监测故障诊断方法,该方法首先在时域内对道旁监测麦克风采集到的轴承声音信号进行时域多普勒校正,有效地解决了由于多普勒效应而带来的轴承声音信号的频移、频带扩展以及幅值调制的问题。然后利用EEMD方法提取蕴含轴承故障特征信息的本征模态信号并计算其包络谱来判断轴承是否存在故障。将该方法用于火车轴承外圈、内圈局部故障状态下的特征提取,结果表明该方法能够有效去除轴承声音信号中的多普勒效应,并能够有效提取列车轴承的故障特征。A new method of wayside acoustic fault diagnosis for locomotive bearings was presented here. With this method, firstly, Doppler effect correction in time domain was implemented for a bearing＇ s acoustic signal recorded by the wayside microphone. Such problems as frequency shift, frequency band expansion and amplitude modulation could be solved through this correction. Secondly, the ensemble empirical mode decomposition （EEMD） method was applied to extract the intrinsic mode functions （IMFs） containing the fault signatures of the bearing. Finally, the envelope spectrum of the selected IMF was calculated to judge if the bearing was defective. This method was applied to extract features of a locomotive bearing with a single defect on the outer race and inner one, respectively. The results showed that the proposed method can reduce Doppler effect embedded in the bearing＇s acoustic signal and can effectively extract the fault features of locomotive bearings.

关 键 词：列车轴承 故障诊断 多普勒校正 EEMD 

分 类 号：TH165.3[机械工程—机械制造及自动化]