Gear fault diagnosis using an improved Reassigned Smoothed Pseudo Wigner-Ville Distribution

Abstract

The work is aimed: (i) to propose a Joint Time-Frequency Analysis method for gear fault diagnosis by using the combined autoregressive model-based filtering and Reassigned Smoothed Pseudo Wigner-Ville Distribution (RSPWVD) methods; (ii) to investigate the use of both vibration and acoustic measurements for fault diagnosis of a gear system by using the proposed fault diagnosis method. To the best of the authors’ knowledge, such RSPWVD method has not been utilized for gearbox applications due to the problem with the complexity of signals generated by the gearbox. For this purpose, experiments on a single-stage spur gearbox were carried out on a gearbox test-rig using single-defect and double-defect gear tooth faults with vibration and non-contact acoustic sensing. It was experimentally demonstrated that the proposed fault diagnosis method performed better compared to the Continuous Wavelet Transform and the Smoothed Pseudo Wigner Ville-Distribution methods. The proposed method is able to provide a more accurate indication of faults in a gearbox, even for the case of multiple gear defects using both acoustic and vibration measurements.

Keywords

• vibration and acoustic sensing
• gear fault diagnosis
• reassignment method
• wigner-ville distribution
• wavelet