Open AccessIdentification of Bearing Faults using Wavelet Transform
Author(s) -
P.K. Vishwakarma,
Ajay Sharma
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d9245.118419
Subject(s) - ringing , wavelet , identification (biology) , computer science , wavelet packet decomposition , bearing (navigation) , ball (mathematics) , wavelet transform , rolling element bearing , electronic engineering , continuous wavelet transform , engineering , acoustics , artificial intelligence , discrete wavelet transform , vibration , physics , mathematics , enhanced data rates for gsm evolution , mathematical analysis , botany , biology
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.