RV reducer fault diagnosis based on order tracking and improved wavelet threshold noise reduction

In view of the characteristics of the vibration signal collected during the swing fatigue test of the RV reducer, the vibration source is complex, the noise influence is strong, and the nonlinear transformation is used. phenomenon, the fault wear point cannot be accurately extracted. In view of the above problems, this paper proposes an order tracking analysis combined with an improved wavelet threshold noise reduction method to extract the fault features of the vibration signal collected during the fatigue test of the RV reducer. Firstly, the collected non-stationary time-domain vibration signal is transformed into the equi-angle domain by the order tracking method; then the equi-angle domain signal is denoised by threshold using the improved wavelet threshold noise reduction method; The signal is subjected to FFT transformation to obtain an order map. Compared with the traditional wavelet noise reduction analysis results, the method can effectively extract the fault information of the internal parts of the RV reducer in the swing fatigue experiment, which provides a basis for the fault diagnosis of variable-speed rotating machinery.