基于EMD和包络分析的城轨列车滚动轴承故障诊断

为了准确识别城轨列车滚动轴承故障类型，研究了一种基于经验模态分解（EMD，Empirical Mode Decomposition）和包络分析的滚动轴承故障诊断方法。对滚动轴承的振动信号进行EMD分解，得到若干个本征模态函数（IMF，Intrinsic Mode Function）之和，对包含主要信息成分的IMF分量作包络分析，根据包络谱的故障特征频率判断滚动轴承故障类型。实验结果表明，该方法能够准确有效地识别城轨列车滚动轴承的故障类型。

Fault diagnosis for rolling bearing of Urban Trnsit trains based on EMD and envelope spectrum

Aiming at the problem of fault diagnosis for rolling bearing of Urban Transit trains, a method combined empirical mode decomposition (EMD) with envelope spectrum was researched on the basis of roller bearing vibration signals. Rolling bearing vibration signals were decomposed into a finite number of intrinsic mode functions(IMFs) by using EMD. Envelope spectrum was used to calculate some IMFs including the main information. Fault pattern was determined by contrast with characteristic defect frequencies of rolling bearing. The experiment result indicated that the fault pattern of rolling bearing could be identified effectively by the researched method.