Multi-Faults Diagnosis of Rotating Bearings Using Flexible Time-Frequency Analysis Technique

• Published in: 2018 International Conference on Sensing,Diagnostics, Prognostics, and Control (SDPC) pp. 347 - 352
• Main Authors: Chunlin Zhang, Binqiang Chen, Fangyi Wan, Bifeng Song
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2018
• Subjects: Fault diagnosis; fault mode distinguish; flexible wavelet transform; multi-faults diagnosis; Rolling bearings; rotating bearing; Time-frequency analysis; Vibrations; Wavelet transforms
• DOI: 10.1109/SDPC.2018.8664933

Multi-faults diagnosis is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, nonstationary structural vibrations and strong background noises. In this paper, a novel, flexible time-frequency (TF) analysis method is proposed to isolate and identify multiple faults occurred in different components of rolling bearings. Employing arbitrary and flexible time-frequency covering manner via fractional scaling and translation factors of the flexible analytical wavelet transform, optimal wavelet basis is constructed which decomposes the original measurements into fine, tunable frequency bands. The sensitive frequency subband which enhance the signal-to-noise ratio of fault features is selected, and is further processed and exhibited in the TF plane to uncover different fault modes. The proposed method is applied to analyze the vibration measurements from locomotive running parts subjected to multi-faults which are arbitrarily fabricated on outrace and roller surfaces of the tapered roller bearings. The results validate the effectiveness of the proposed method in isolating and identifying the multiple faults.