Search:
Computing and Library Services - delivering an inspiring information environment

Componential coding in the condition monitoring of electrical machines Part 2: application to a conventional machine and a novel machine

Payne, B.S., Gu, Fengshou, Webber, C J S and Ball, Andrew (2003) Componential coding in the condition monitoring of electrical machines Part 2: application to a conventional machine and a novel machine. Proceedings of the Institute of Mechanical Engineering Part C, Journal of Mechanical Engineering Science, 217 (8). pp. 901-915. ISSN 0954-4062

[img]
Preview
PDF - Published Version
Download (4083kB) | Preview

    Abstract

    This paper (Part 2) presents the practical application of componential coding, the principles of which were described in the accompanying Part 1 paper. Four major issues are addressed, including optimization of the neural network, assessment of the anomaly detection results, development of diagnostic approaches (based on the reconstruction error) and also benchmarking of componential coding with other techniques (including waveform measures, Fourier-based signal reconstruction and principal component analysis). This is achieved by applying componential coding to the data monitored from both a conventional induction motor and from a novel transverse flux motor. The results reveal that machine condition monitoring using componential coding is not only capable of detecting and then diagnosing anomalies but it also outperforms other conventional techniques in that it is able to separate very small and localized anomalies.

    Item Type: Article
    Subjects: T Technology > T Technology (General)
    T Technology > TJ Mechanical engineering and machinery
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
    School of Computing and Engineering > Informatics Research Group
    School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
    Related URLs:
    Depositing User: Sharon Beastall
    Date Deposited: 20 Jan 2010 14:04
    Last Modified: 08 Dec 2010 13:35
    URI: http://eprints.hud.ac.uk/id/eprint/6810

    Document Downloads

    Downloader Countries

    More statistics for this item...

    Item control for Repository Staff only:

    View Item

    University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©