Abstract
A novel practical technique for bearing defect detection and recognition based on cyclic modulation spectrum (CMS) is presented. Cyclic modulation spectrum stands as a much faster method to detect periodic modulation feature and has a lower complexity. CMS has a very fast calculation speed, but it can provide similar results with spectral correlation density. This advantage enables the cyclic modulation spectrum to extract useful information from the noisy environment in rotating machine. The validity of this technique is exhibited on bearing defect vibration data from an industrial gearbox. The results show the advantage of cyclic modulation spectrum. CMS can correctly pick up the transient features from interference signals and can accurately recognize the rolling element bearing defect.
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