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Publication Type : Journal Article
Publisher : IJMET
Source : International Journal of Mechanical Engineering & Technology (IJMET), Volume 1, Issue 1, p.38–48 (2010)
Url : https://d1wqtxts1xzle7.cloudfront.net/30882619/WAVELET_DESIGN.pdf?1362664099=&response-content-disposition=inline%3B+filename%3DWAVELET_DESIGN_FOR_FAULT_DIAGNOSIS_OF_RO.pdf&Expires=1618810088&Signature=QRlqEXcuL7w0RqEqWnWB9X5BYVcB2xaA-lz2igxs6QknQxGjZXLVA
Keywords : Continuous Wavelet Transform, Fault diagnosis, New Wavelet design
Campus : Amritapuri
School : School of Arts and Sciences
Department : Mathematics
Year : 2010
Abstract : Fault diagnosis of the roller bearings plays an important role in machine condition monitoring. Researchers are trying to perform the fault diagnosis using machine learning approach. However, there are alternate methods of doing the same. This paper presents the methodology for designing a new wavelet using continuous wavelet transforms. The time domain signals of good bearing is alone required for this study. For the sake of study purpose, three different faults were simulated on to the bearings and the corresponding time domain signals were acquired. The newly designed wavelet gives a classification accuracy of 83.25% in classifying bearing conditions.
Cite this Research Publication : Manju B. R., Rajan, A. R., and Sugumaran, V., “Wavelet design for fault diagnosis of roller bearings using continuous wavelet transforms”, International Journal of Mechanical Engineering & Technology (IJMET), vol. 1, no. 1, pp. 38–48, 2010.