基于加窗振动分离和变分模态分解的行星轮故障特征提取

行星齿轮箱振动信号复杂且其传递路径具有时变性,导致故障特征提取困难。针对该问题,提出基于加窗振动分离和变分模态分解(VMD)的行星轮故障特征提取方法。首先利用角域同步平均消除非同步分量;随后对平均后的振动信号进行加窗分离;采用观察中心频率的方法确定参数K,然后对分离的振动信号进行VMD分解并选取包含故障的特征分量;最后对选取的特征分量进行Hilbert解调分析实现故障特征提取。通过行星轮齿根裂纹故障实测信号分析,验证该方法能有效提取行星轮故障特征。

Fault feature extraction of the planet gear based on windowed vibration separation and variational mode decomposition

The vibration signal of planetary gearboxes is complex with time varying transmission paths, which makes fault feature extraction of planetary gearboxes difficult. For this issue, a fault feature extraction method based on windowed vibration separation and variational mode decomposition (VMD) is proposed. Firstly, the angle synchronous average is used to eliminate asynchronous components. Then, the windowed vibration separation is implemented. The parameter K is determined by observing the center frequency, and the VMD is applied to separated vibration signals to select the component containing fault feature. Finally, the selected feature component is demodulated by Hilbert demodulation analysis to achieve the fault feature extraction. By analyzing the measured signal of planet gear root crack fault, it is proved that this method can effectively extract the fault feature of the planet gear.