转频阶比大时间尺度在时变工况下齿轮局部故障识别中的应用

APPLICATION OF FREQUENCY ORDER-LARGE TIME SCALE TO LOCAL FAULT IDENTIFICATION OF GEAR UNDER TIME-VARYING CONDITIONS

为进一步提高Vold-Kalman阶比跟踪(Vold-Kalman filter based order tracking,VKF-OT),结合去趋势波动分析(detrended fluctuation analysis,DFA)算法在时变工况下齿轮局部故障的特征区分度,提出一种以转频阶比分量为研究对象的大时间尺度特征提取方法。该方法以齿轮转频和啮频作为VKF-OT的提取频率,获取任意时变工况下的2类阶比信号,分析对比两类信号携带的尺度指数特性及其物理意义,发现转频成分相对啮频信号具有更优的局部故障表征能力,而与大时间尺度对应的小尺度指数相较于大尺度、全尺度指数具有更佳的状态区分度。最后以齿轮不同工作状态下的150组振动信号作为验证,结果表明提取的转频阶比大时间尺度特征更利于任意时变工况下的齿轮局部微弱故障的识别。

In order to further improve the distinction degree between characteristics of VKF-OT and DFA algorithm under time-varying conditions,a large time-scale feature extraction method is proposed,which takes rotation frequency order signal as the main research object.The method takes rotation and mesh frequency as the extraction frequency of VKF-OT to obtain two kinds of order signals under any time-varying conditions.By analyzing and comparing the scale index characteristics and physical meaning of two kinds of signals,it is found that rotation frequency order signal has better representation ability than that of meshing frequency signal,and the small scale index corresponding to the large time scale has better state discrimination than that of the large scale and full scale index.Finally,150 sets of vibration signals of gear under different working conditions are taken as verification objects.The results show that the extracted frequency orderlarge time scale is more conducive to the identification of the partial weak faults in the gear under arbitrary changing conditions.