Fault Diagnosis of Planetary Gearbox Based on Time Series Analysis

The environmental conditions of the gearbox operation will cause strong noise during signal acquisition, so a time-series method is proposed to perform fault diagnosis on the gearbox. Compared to the traditional spectrum analysis, we can see that the time series analysis has a better recognition ability for gearbox fault diagnosis by using time series analysis to investigate the spectrum of the planetary gearbox. Through the data acquisition system designed by Labview virtual instrument, the data is collected to extract feature signals. Then the AR model is used to determine the order of the model. Finally, the AR model parameter algorithm is used to determine the tolerance range of the gear parameters under normal conditions. When the order is unchanged, the model parameters of the fault signal are analyzed, and then compared with the tolerance range of the normal parameters to diagnose the fault of the gearbox. It indicates that the proposed method has a significant effect on gear diagnosis.