An improved spectrum correlation time-frequency analysis method and its application in fault diagnosis of rolling element bearing

The spectrum correlation (SC) is an effective fault feature extraction method for rolling bearing which is based on second order cyclic statistic. However, the effectiveness of SC will be compromised greatly when the rolling bearing fault feature signal is interfered by noise. To solve the problem, the SC method is improved and the improved spectrum correlation (ISC) method is proposed in the paper, and the noise-resistance virtue of ISC compared with SC is verified through the accelerated fatigue and compound fault test of rolling element bearing. Besides, the vibration signal of fault rolling bearing takes on modulation phenomenon, and extracting the fault characteristic frequency (FCF) or cyclic modulation frequency (CMF) is enough for the purpose of fault diagnosis, and the modulation frequency is neglected usually. However, the extraction result of ISC is not intuitive enough because it extracts the FCF and modulation frequency with its harmonic synchronously. To improve the intuitive feature extraction effect of ISC, the ISC method is improved further in the paper and the integrated improved spectrum correlation (IISC) is proposed which would only extract the FCF or CMF, so much clear and better extraction effectiveness could be obtained by IISC method, and the effectiveness and better fault extraction results by applying IISC method on vibration data of rolling bearing accelerated fatigue and compound fault test are also presented