Vibration modelling and fault evolution symptom analysis of a planetary gear train for sun gear wear status assessment

Abstract

The diagnosis and monitoring of surface wear are very critical for the prevention of shutdown and even catastrophic destruction of a geared transmission system. However, the detection for the evolutionary status of surface wear in a planetary gear train is quite challengeable due to the complicated and weak characteristics buried in the vibration signals. To assess the wear status of gears in a planetary gear train, a sophisticated vibration signal analysis based methodology is proposed. First, an analytical dynamic model of single-stage planetary gear train is established, which incorporates the effects of distributed surface wear of mating gears. With the analytical dynamic model, a resultant vibration signal model is further established after considering the influences of transfer path, direction variation of gear action lines and background noise. This vibration signal model is used to represent the actual vibration signals collected by transducers installed on the housing of planetary gearbox. Based on the constructed resultant vibration signals, two novel fault indicators are defined to reveal the evolution law of fault symptom. The fault evolution symptom analysis is used to identify healthy status and wear status of mating gears in the planetary transmission system. The effectiveness of the proposed model as well as the fault indicators are validated by both simulated signals and experimental signals.