基于局部均值分解的阶次跟踪分析及其在齿轮故障诊断中的应用

Order Tracting Analysis Based on Local Mean Decomposition and Its Applications to Gear Fault Diagnosis

针对齿轮升降速过程中故障振动信号为多分量的调制信号以及故障特征频率随转速变化的特点,将局部均值分解(LMD)与阶次跟踪分析相结合,提出了一种新的齿轮故障诊断方法。首先采用阶次重采样将齿轮的时域振动信号转换为角域平稳信号,然后对角域信号进行LMD分解,得到若干个乘积函数(PF)分量,最后对各个PF分量的瞬时幅值进行频谱分析来提取齿轮的故障特征。通过对齿轮齿根裂纹故障试验振动信号的分析可知,该方法能有效地提取齿轮故障特征。

Gear fault vibration signals in speed up or speed down processes were of multi-component modulated signals and the fault characteristic frequency varied with rotating speed.A new gear fault diagnosis method combined LMD with order tracking analysis was proposed.Firstly,the vibration signals in time domain were transformed into angle domain stational signals by order resampling.Then,a set of product functions（PF） were obtained by decomposed the signals in angle domain with LMD.At last,each PF＇s instantaneous amplitude was analyzed by frequency spectrum to extracting the fault characteristics.The analysis results from the experimental fault vibration signals of gear crack demonstrate this method can extracted the gear fault charateristics effectively.