A low-frequency fault detection method for low-speed planetary gearbox based on acoustic signals

• A new low-frequency fault detection method is proposed. • The proposed method overperforms wavelet decomposition method in weak feature extraction. • The acoustic signals present more significant fault features than vibration signals. • The effect of feature extraction is evaluated quantitatively. In some practical application of construction machinery and equipment, the planetary gearbox in the walking parts is wrapped with tires, and its speed is very low. When this planetary gearbox fails, the fault frequency is very low (less than 1 Hz) due to its complex transmission relationship. Because the planetary gearbox has the characteristics of low speed, low fault frequency and surrounded by tires, it is difficult to detect its fault condition in practical engineering. This work proposes a new low-frequency fault detection method. First, the pre-processing is used for the measured acoustic signals. Second, the pre-processed acoustic signals are decomposed into components by the multi-resolution singular value decomposition. Third, the autoregressive model is constructed to select fault-related component. Finally, the output component is further analyzed by envelope spectrum analysis. The results indicate that the proposed method can accurately detect the characteristic information of low frequency faults of planetary gearbox in practical engineering.