Fault diagnosis of low-speed shafts in large gearboxes based on wavelet analysis

Aimed at the difficulty to extract the fault information of a low speed shaft in a large gearbox, wavelet analysis was used to realize the local analysis of signals in a time and frequency domain simultaneously. The signals were dissembled to a series of compactly supported wavelet bases non-redundantly and without leaking. The saltation coefficient of wavelet analysis was regarded as a characteristic value to predict a sudden accident and the changing trend of the coefficient was figured out. The results showed that wavelet transform could capture the characteristics in a time domain and the evolvement procedure of a fault. The trend graph of the coefficient could effectively predict the development trend of a fault and avoid a sudden accident.