基于振动信号分离的行星轴承故障特征提取

由于行星轴承振动信号传递路径的时变性,且行星齿轮箱中齿轮啮合振动信号较强,导致行星轴承故障特征提取较为困难。为此,提出了一种基于振动信号分离的行星轴承故障特征提取方法。该方法首先采用阶比分析技术将原始振动信号进行等角度采样;每当行星架旋转一周,采用Tukey窗进行加窗截取,按照啮合齿序重新拼接,构造振动分离信号。再采用离散随机分离从振动分离信号中提取行星轴承故障分量;最后进行包络谱分析提取故障特征。行星轴承内圈故障实测信号分析表明,该方法能有效提取行星轴承故障特征。

Fault feature extraction of planet bearings based on vibration signal separation

Due to planet bearings vibration signals’ time-varying transmission path, and stronger meshing vibration signals in a planetary gearbox, fault feature extraction of planet bearings is more difficult.  Here, a fault feature extraction method of planet bearings based on vibration signal separation was proposed. Firstly, an original vibration signal was isometrically sampled with the order analysis technology. Secondly, a Tukey window was used for windowing interception during planet carrier rotating each revolution. The intercepted signals were reassembled according to meshing teeth sequence to construct vibration separation signals. Then, the discrete random separation technology was utilized to extract fault components of a planet bearing from vibration separation signals. Finally, fault features were extracted with the envelope spectral analysis from fault components. Analyses for actual measured signals of planet bearing inner race faults showed that the proposed method can effectively extract fault features of planet bearings.