基于局部均值分解的循环频率和能量谱在齿轮故障诊断中的应用

Application of cycle frequency and energy spectrum based on local mean decomposition to gear fault diagnosis

针对齿轮故障振动信号的非平稳特性,将局部均值分解(Local mean decomposition,LMD)引入齿轮故障诊断,提出了基于LMD的循环频率和能量谱概念,并根据齿轮故障振动信号的特点建立了两种齿轮故障诊断方法:基于LMD的循环频率方法和局部能量谱方法。采用LMD方法能将齿轮振动信号自适应地分解为若干个单分量信号,而循环频率和能量谱则分别反映了齿轮振动信号的相位调制信息以及信号能量在时频面上的分布情况,从而可以提取出齿轮振动信号的故障特征。将这两种方法应用于实际齿轮箱的故障诊断中,结果表明两种方法都能有效地提取齿轮故障特征信息。

Aiming at the nonstationary characteristic of the gear fault vibration signal,the local mean decomposition is introduced into gear fault diagnosis.Then the concept of cycle frequency and energy spectrum based on local mean decomposition is proposed and two new gear fault diagnosis methods named cycle frequency and local energy spectrum based on LMD are established according to the characteristic of gear fault vibration signal.The gear vibration signal can be decomposed into a set of single-component signals by using LMD.And that the cycle frequency and energy spectrum can reflect the phase modulated information of gear vibration signal and energy distributing conditions in time-frequency domain respectively,thereby the fault characteristic of gear vibration signal can be extracted from it.These two methods have been applied to actual gearbox fault diagnosis.The analysis results demonstrate these two methods can both extract the gear fault characteristic effectively.