基于包络谱分析的航空发动机主轴轴承故障诊断

Fault diagnosis of aero-engine main shaft bearings based on envelope spectrum analysis

针对某型航空发动机地面检测条件下采集到的机匣振动信号,利用小波变换和包络分析相结合的方法提取主轴轴承故障信息并进行故障诊断。首先对所采集到的航空发动机振动信号进行小波降噪,再利用小波变换提取降噪后的滚动轴承故障特征信号,然后对该故障特征频段进行包络谱分析,以获得特征峰值频率。将该方法应用到试验数据中,分析发现该方法能够有效地诊断出航空发动机主轴轴承故障及具体的故障位置。这为航空发动机主轴轴承故障诊断提供了重要的判断依据,具有广阔的应用前景。

A method combining wavelet transform and envelope spectrum is proposed for the collection of fault information and the fault diagnosis for the aero-engine main shaft bearings, taking advantage of the recorded aero-engine vibration signals collected from the ground tests. First, the recorded aero-engine vibration signals are wavelet de-noised; then, the wavelet de-noised fault feature signals are extracted through wavelet transform; lastly, the fault feature signals are analyzed through the Hilbert envelope spectrum to obtain the characteristic peak frequencies. After being applied in tests, this method is approved to be effective in the diagnosis of the fault and the definite fault position of the aero-engine main shaft bearings, which may provide a virtual basis on the fault diagnosis of aero-engine main shaft bearings and has a broad prospect of application.