Spectrum auto-correlation analysis and its application to fault diagnosis of rolling element bearings

• Published in: Mechanical systems and signal processing Vol. 41; no. 1-2; pp. 141 - 154
• Main Authors: Ming, A.B., Qin, Z.Y., Zhang, W., Chu, F.L.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-12-2013
• Subjects: Autocorrelation; Bearings; Cyclostationary analysis; Envelopes; Failure; Fault diagnosis; Faults; Incipient fault; Mechanical systems; Oscillations; Rolling element bearings; Spectral auto-correlation analysis; Squared envelope analysis; Cyclostationary analysis; Rolling element bearings; Spectral auto-correlation analysis; Squared envelope analysis; Incipient fault
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2013.08.004

Bearing failure is one of the most common reasons of machine breakdowns and accidents. Therefore, the fault diagnosis of rolling element bearings is of great significance to the safe and efficient operation of machines owing to its fault indication and accident prevention capability in engineering applications. Based on the orthogonal projection theory, a novel method is proposed to extract the fault characteristic frequency for the incipient fault diagnosis of rolling element bearings in this paper. With the capability of exposing the oscillation frequency of the signal energy, the proposed method is a generalized form of the squared envelope analysis and named as spectral auto-correlation analysis (SACA). Meanwhile, the SACA is a simplified form of the cyclostationary analysis as well and can be iteratively carried out in applications. Simulations and experiments are used to evaluate the efficiency of the proposed method. Comparing the results of SACA, the traditional envelope analysis and the squared envelope analysis, it is found that the result of SACA is more legible due to the more prominent harmonic amplitudes of the fault characteristic frequency and that the SACA with the proper iteration will further enhance the fault features.
•A feature extraction method is proposed for the bearing fault diagnosis.•The proposed method is the simplification of the cyclostationary analysis.•The proposed method could be iteratively carried out to enhance the fault feature.•Simulated and experimental signals are used to verify the fault diagnosis efficacy.