Fast Cmspogram: An effective new tool for periodic pulse detection

Bearings are the most critical and vulnerable components in rotating machinery. Periodic impulses will be generated when a bearing is operating under a damage condition. Spectral kurtosis (SK) is considered to be an effective tool for impulse detection. However, under certain situations such as in the presence of random noise or signals containing only a single impulse, SK may yield a poor detection result. A periodic impulse detection method termed as cyclic modulation spectrum peak (CMSP) is thus proposed in this work to suppress the effects of random noise, single impulse and other disturbances to detect periodic impulses in condition monitoring signals for bearing fault diagnosis. CMSP is to identify the periodic characteristics of a signal by finding the maximum peak in CMS, that is, the main periodic component or main period in the signal. To further extract the periodic impulse information in the signal, a decomposition method termed as fast Cmspogram (FC), similar to that of fast Kurtogram (FK) is proposed. FC is as accurate as CMPS in identifying the center frequency of periodic impulse signals, so FC can obtain more periodic impulse information when demodulating the selected resonant frequency band. The accuracy and validity of the proposed method is examined using both simulated signals and experimental data. The results show that the method can be applied for an accurate bearing fault diagnosis in across a wide range of typical application scenarios.