Identification of Bearing Faults using Wavelet Transform
Ajay Sharma1, Prem Narayan Vishwakarma2
1Prem Narayan Vishwakarma, Assistant Professor Mechanical Engineering Department Amity School of Engineering & Technology Amity University, Noida U.P India.
2Ajay Sharma, Assistant Professor Mechanical Engineering Department Amity School of Engineering & Technology Amity University, Noida U.P India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 9829-9833 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9245118419/2019©BEIESP | DOI: 10.35940/ijrte.D9245.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research is concerned with description of a scheme for bearing’s localized defect detection based on wavelet packet transform (WPT). WPT provides a high resolution time-frequency distribution from which periodic structural ringing due to repetitive force impulses, generated upon the passing of each rolling element on the defect, are detected. The objective of this work is to emphasis on the outer race defect, inner race defect and ball defect. In modern industrial scenario, there is increasing demand for automatic condition monitoring that reduce the gap between digital model and actual product. With reliable condition monitoring, faults such as machine element failures could be identified in their early-stages and further damage to the system could be prevented. Successful monitoring is a complex and application-specific problem, but a generic tool would be useful in preliminary analysis of new signals and in verification of known theories.
Keywords: Bearings, Condition Monitoring, Diagnosis, Fault Detection, Wavelet Packet Transform (WPT), Root Mean Square Value (rms) and Machine Health Condition Monitoring (MHCM).
Scope of the Article: Aggregation, Integration, and Transformation.