A comparison of the performance of radial basis function and multi-layer perceptron networks in condition monitoring and fault diagnosis applications

Yuhua Li, MJ Pont, NB Jones

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

    Abstract

    In this paper, we provide a detailed comparison of multi-layer Perceptron (MLP) and radial basis function (RBF) networks in embedded, microcontroller-based condition monitoring and fault diagnosis applications. On the basis of the studies presented here, it is concluded that the MLP provides similar levels of performance to the RBF network while exerting a low computational load on the processor.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    Pages577-592
    Number of pages6
    Publication statusPublished - 1999
    EventCONDITION MONITORING `99, PROCEEDINGS - SWANSA, WALES
    Duration: 1 Jan 1999 → …

    Conference

    ConferenceCONDITION MONITORING `99, PROCEEDINGS
    Period1/01/99 → …

    Keywords

    • engine misfire detection
    • neural networks
    • multi-layer perception
    • radial basis function
    • condition monitoring
    • fault classification

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