Fault diagnosis of motor bearing with speed fluctuation via angular resampling of transient sound signals. (22nd December 2016)

• Record Type: Journal Article
• Authors: Lu, Siliang; Wang, Xiaoxian; He, Qingbo; Liu, Fang; Liu, Yongbin
• Is Part Of: Journal of sound and vibration. Volume 385(2016)
• Page Start: 16
• Page End: 32
• Publication Date: 2016-12-22
• Subjects: Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2016.09.012
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: Transient signal analysis (TSA) has been proven an effective tool for motor bearing fault diagnosis, but has yet to be applied in processing bearing fault signals with variable rotating speed. In this study, a new TSA-based angular resampling (TSAAR) method is proposed for fault diagnosis under speed fluctuation condition via sound signal analysis. By applying the TSAAR method, the frequency smearing phenomenon is eliminated and the fault characteristic frequency is exposed in the envelope spectrum for bearing fault recognition. The TSAAR method can accurately estimate the phase information of the fault-induced impulses using neither complicated time-frequency analysis techniques nor external speed sensors, and hence it provides a simple, flexible, and data-driven approach that realizes variable-speed motor bearing fault diagnosis. The effectiveness and efficiency of the proposed TSAAR method are verified through a series of simulated and experimental case studies. Highlights: Propose a sound analysis-based motor bearing fault diagnosis method. Sound signal is segmented using short-time energy endpoint detection. Segment signal parameters identification using transient modeling. Collision instants of fault-induced impulses are located. Original sound signal is angular resampled for fault diagnosis.