Characteristic enhancement of RV reducer under non-stationary condition based on WDT-IF-SS-VMD

Abstract

Abstract Because the working conditions of the rotate vector (RV) reducer are often reciprocating at variable speeds and the working environment is relatively complex, so the vibration signals collected have non-stationary vibration and complex environmental noise. A fault diagnosis method for RV reducer (WDT-IF-SS-VMD) is proposed, which combines instantaneous frequency (IF) trend graph based on current signal and the parameter adaptive variational mode decomposition (VMD) algorithm. Firstly, the current signal and vibration signal are collected synchronously, and the steady-state phase of vibration signal is intercepted according to the IF trend diagram obtained by wavelet decomposition transform (WDT) of the current signal. Secondly, the intercepted vibration signals are transformed into scale space, and the parameters of VMD are selected adaptively based on fuzzy C-means clustering. Then, the maximum kurtosis criterion is used to complete the extraction of sensitive components. Finally, the envelope analysis is carried out to complete the fault diagnosis. The measured signal analysis results show that this method can effectively separate and extract fault features of the RV reducer.