Anomaly detection of rolling elements using fuzzy entropy and similarity measures

M. L. Dennis Wong, S. H. Lee, A. K. Nandi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The ability of detecting faults in rotating elements is highly desired in machine condition monitoring application (MCM). On many MCM platforms, discriminating attributes based on time and/or frequency domain of the acquired vibration data are used to classify the element under monitoring into normal and abnormal conditions. However, having such diagnostic ability is still insufficient in our global goal towards predictive maintenance. To achieve true predictive maintenance, the development tool must be able to provide a certain level of real time computation capability. In this paper, the authors propose a novel method based on fuzzy entropy and similarity measure for monitoring the health conditions of ball bearings on-line. The practicalities of the effectiveness and speed of the method are verified empirically, and results are presented towards the end of this paper.

Original languageEnglish
Title of host publicationInstitution of Mechanical Engineers
Subtitle of host publication10th International Conference on Vibrations in Rotating Machinery
Place of PublicationCambridge, United Kingdom
PublisherWoodhead Publishing Ltd.
Pages693-702
Number of pages10
ISBN (Electronic)9780857094537
ISBN (Print)9780857094520
Publication statusPublished - 11 Sep 2012
Event10th International Conference on Vibrations in Rotating Machinery 2012 - London, United Kingdom
Duration: 11 Sep 201213 Sep 2012
Conference number: 10
http://events.imeche.org/ViewEvent?code=c1326# (Conference website)

Conference

Conference10th International Conference on Vibrations in Rotating Machinery 2012
Abbreviated titleVIRM10
CountryUnited Kingdom
CityLondon
Period11/09/1213/09/12
Internet address

ASJC Scopus subject areas

  • Mechanical Engineering

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  • Cite this

    Wong, M. L. D., Lee, S. H., & Nandi, A. K. (2012). Anomaly detection of rolling elements using fuzzy entropy and similarity measures. In Institution of Mechanical Engineers: 10th International Conference on Vibrations in Rotating Machinery (pp. 693-702). Woodhead Publishing Ltd..