A novel vibro-acoustic fault diagnosis approach of planetary gearbox using intrinsic wavelet integrated GE-EfficientNet

Abstract

Planetary gearbox operates under complex working conditions involving high speed, heavy load, and corrosion. When the planetary gearbox is in tight spaces, it is difficult to measure its signal by conventional methods. In this case, acoustic sensors can measure signal with the noncontact method. This paper proposes a vibro-acoustic fault diagnosis method with respect to planetary gearbox. The method addresses challenges related to weak vibro-acoustic signal, difficulty in extracting fault features, and low diagnostic accuracy and efficiency. Firstly, vibro-acoustic signal is captured by a unidirectional microphone. Next, intrinsic wavelet analysis extracts intrinsic features of the planetary gears. The band-limited intrinsic mode functions (BLIMFs) of the acoustic signal are obtained by optimized variational mode decomposition, and the BLIMFs are then transformed into time-frequency map features. Finally, these time-frequency map features are utilized as the inputs for Ghost module and Efficient channel attention module (GE)-improved EfficientNet model, namely GE-EfficientNet model, to achieve fault diagnosis of planetary gearbox. The superiority of the proposed method is verified by the experimental results which show that the diagnostic accuracy of GE-EfficientNet reached 100%, and the floating-point operations and parameter numbers are only 5.1 G and 0.4 MB, respectively. The results demonstrate that the proposed vibro-acoustic fault diagnosis method achieves good diagnostic accuracy and efficiency.