Abstract
Monitoring of incipient faults is vital for the safe and reliable operation of rolling element bearings. In this paper, the combination of discrete wavelet transform and envelope analysis is proposed to extract the characteristic spectrum of rolling bearing vibration data. Then spectrum cross-correlation coefficient is applied to identify different operating conditions of rolling bearings. The proposed method is applied to fault diagnosis of rolling bearings with several different faults. The results show that the proposed method has high classification accuracy, and performs better than alternative approaches based on conventional characteristic defect frequency extraction.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
