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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/46525
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dc.contributor.authorAl-Raheem, K.-
dc.contributor.authorRoy, A.-
dc.contributor.authorRamachandran, K.-
dc.contributor.authorHarrison, O.-
dc.contributor.authorGrainger, S.-
dc.date.issued2006-
dc.identifier.citationICSP'06 : 2006 8th International Conference on Signal Processing : proceedings, November 16-20, 2006, Guilin, China / Yuan Baozong, Ruan Qiuqi, Tang Xiaofang (eds.)-
dc.identifier.isbn0780397363-
dc.identifier.isbn9780780397378-
dc.identifier.urihttp://hdl.handle.net/2440/46525-
dc.description© Copyright 2008 IEEE-
dc.description.abstractRolling bearing fault detection approach using wavelet de-noising technique based on optimized wavelet-base function derived from the impulse response of the bearing system is proposed. The wavelet parameters are optimized based on maximization kurtosis criteria to ensure large similarity with the impulse generated by incipient bearing fault.-
dc.language.isoen-
dc.publisherIEEE Press-
dc.source.urihttp://dx.doi.org/10.1109/icosp.2006.346065-
dc.titleDetection of the Rolling Element Bearing Faults using Optimized Wavelet De-Noising Technique-
dc.typeConference paper-
dc.contributor.conferenceInternational Conference on Signal Processing (8th : 2006 : Beijing, China)-
dc.identifier.doi10.1109/ICOSP.2006.346065-
dc.publisher.placeOnline-
pubs.publication-statusPublished-
dc.identifier.orcidGrainger, S. [0000-0003-4664-7320]-
Appears in Collections:Aurora harvest
Mechanical Engineering publications

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