Induction motor stator current analysis for planetary gearbox fault diagnosis under time-varying speed conditions

Abstract

Vibration-based planetary gearbox fault diagnosis under time-varying speed conditions is challenging. This work exploits the advantages of motor stator current signal in easier accessibility and simpler frequency modulation structure, and applies the motor current signature analysis technique on planetary gearbox fault diagnosis. Firstly, the induction motor stator current signal with both planetary gearbox fault and airgap eccentricity under time-varying speed conditions is analytically modeled, and properties of time-varying planetary gearbox fault signatures are summarized. Then, to address the difficulties of revealing and presenting relatively weak and time-varying fault signatures in motor stator current signal, the adaptive iterative generalized demodulation is utilized. The Fourier transform surrogate test is integrated with iterative generalized demodulation algorithm to solve the problem of weak fault signature extraction, and Hilbert spectra of validated mono-components finally compose the time-frequency representation of analyzed motor stator current signal. Both numerical simulation as well as lab experimental evaluations in different gear fault cases, have been conducted to verify the correctness of the derived time-varying gear fault signatures, and the effectiveness of accurate planetary gearbox fault diagnosis.