Generalized demodulation method based on multi-scale chirplet and sparse signal decomposition and its application to roller bearing fault diagnosis

A new generalized demodulation method based on multi-scale chirplet and sparse signal decomposition is proposed and applied to the bearing fault diagnosis under non-stationary rotating speed. Firstly, the multi-component signal is decomposed by using of the sparse signal decomposition based on multi-scale chirplet and the mono-component signals and its phase functions are obtained. Then, based on the obtained phase functions of mono-component signals, the generalized demodulation method is used to transform the original non-stationary signals into stationary signals. When the rotating speed of a bearing is varying with time, the bearing fault characteristic frequency that follow curves are non-stationary signals. In the proposed method, the non-stationary enveloping signals of bearing fault vibration signals are transformed into stationary signals by using of the generalized demodulation method based on multi-scale chirplet and sparse signal decomposition. According to the relationships between the frequencies of enveloping signals after generalized demodulation and the rotational frequency, faults of the bearing can be identified. Simulation and practical application examples have proved that the proposed method is more effective than the conventional enveloping spectral analysis technique in extracting the features of roller bearing fault vibration signals. © 2010 Chin. Soc. for Elec. Eng.