Application Of Wavelet Transform For Fault Diagnosisof Rolling Element Bearings

The rolling element bearingsare most critical components in a machine. Condition monitoring and fault diagnostics of these bearings are of great concern in industries as most rotating machine failures are often linked to bearing failures. This paper presents a methodology for fault diagnosis of rolling element bearings based on discrete wavelet transform (DWT) and wavelet packet transform (WPT). In order to obtain the useful information from raw data,db02 and db08 wavelets were adopted to decompose the vibration signal acquired from the bearing. Further Denoising technique based on wavelet analysis was applied. This de-noised signal was decomposed up to 7th level by wavelet packet transform (WPT) and 128 wavelet packet node energy coefficients were obtained and analyzed using db04 wavelet.The results show that wavelet packet node energy coefficients are sensitive to the faults in the bearing. The feasibility of the wavelet packet node energy coefficients for fault identification as an index representing the health condition of a bearing is established through this study.

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