Adaptive timefrequency filtering method based on CPP and S transform and its application in fault diagnosis of rolling bearing

Aiming at extracting and separating fault modulation message of rolling bearing under variable rotational speed, an adaptive timefrequency filtering method based on chirplet path pursuit (CPP) and S transform was proposed. In this method, the envelope of vibration signal of a gearbox was obtained by Hilbert demodulation, and the S transform was carried out for the envelope signal so as to get its timefrequency distribution, meanwhile, the CPP algorithm was used to estimate the gear mesh frequency from the vibration signal of a gearbox, then, the shaft rotational speed can be got. According to the shaft rotational speed, each adaptive timefrequency filter was designed. Then the timefrequency filtering was carried out for the timefrequency distribution of envelope signal, and the S inverse transform was used for the filtered results so as to get each fault demodulation signal. Lastly, the order spectrum analysis was carried out for each fault demodulation signal, and the fault of rolling bearing was diagnosed according to the demodulation information in order spectrum. Simulation and application examples indicate that the adaptive timefrequency filtering method can adaptively change the filters center frequency and bandwidth according to the frequency variation characteristics of the rolling bearings fault modulation signal, and also can effectively extract and separate each order demodulation message of rolling bearing, besides, it has better separation effect than the ensemble empirical mode decomposition(EEMD) based order spectrum method.