Fault diagnosis of planetary gearbox based on acoustic signals

The reliability of planetary gearbox is extremely important for safe and reliable operation. In this work, a fault diagnosis method based on acoustic signals is proposed for planetary gearbox, where the generated acoustic signals are nonlinear and non-stationary. First, the Fourier decomposition method (FDM) is utilized to decompose the measured acoustic signals into Fourier intrinsic band functions (FIBFs). Compared with the traditional empirical mode decomposition (EMD) method, FDM has better decomposition effect results without end effects and mode aliasing issues. Second, the comprehensive feature parameters of energy and TESK (time and envelope spectrum kurtosis) are adopted for overcoming the noisy and weak acoustic signals. Compared with a single feature parameter, the comprehensive feature parameters can significantly improve the accuracy of fault diagnosis. Third, the Random Forest (RF) classification algorithm is adopted for setting up the fault diagnosis method. Experimental results show that the fault diagnosis accuracy rate of the proposed FDM-based method using the acoustic signals reaches up to 96.32% under the limited sample data conditions, which achieved better fault diagnosis effect than vibration signals in the experimental conditions. (C) 2021 Elsevier Ltd. All rights reserved.