Investigation on Planetary Bearing Weak Fault Diagnosis Based on a Fault Model and Improved Wavelet Ridge

Abstract

Rolling element bearings are of great importance in planetary gearboxes. Monitoring their operation state is the key to keep the whole machine running normally. It is not enough to just apply traditional fault diagnosis methods to detect the running condition of rotating machinery when weak faults occur. It is because of the complexity of the planetary gearbox structure. In addition, its running state is unstable due to the effects of the wind speed and external disturbances. In this paper, a signal model is established to simulate the vibration data collected by sensors in the event of a failure occurred in the planetary bearings, which is very useful for fault mechanism research. Furthermore, an improved wavelet scalogram method is proposed to identify weak impact features of planetary bearings. The proposed method is based on time-frequency distribution reassignment and synchronous averaging. The synchronous averaging is performed for reassignment of the wavelet scale spectrum to improve its time-frequency resolution. After that, wavelet ridge extraction is carried out to reveal the relationship between this time-frequency distribution and characteristic information, which is helpful to extract characteristic frequencies after the improved wavelet scalogram highlights the impact features of rolling element bearing weak fault detection. The effectiveness of the proposed method for weak fault recognition is validated by using simulation signals and test signals.