Identification and fault diagnosis of an industrial gas turbine prototype model.

Silvio Simani, Ron J. Patton, Steve Daley, Andrew Pike

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    4 Citations (Scopus)

    Abstract

    This paper addresses a model-based procedure exploiting analytical redundancy for the detection and isolation of faults of a power plant. The residual generation is performed by means of output observers and Kalman filters in connection with the uncertainty affecting the measurements acquired from the monitored system. The model of the process under investigation required to design observers and filters is obtained by identification. The proposed fault detection and isolation tool has been tested on a simulated model of an industrial gas turbine prototype.
    Original languageEnglish
    Title of host publicationProceedings of the 39th IEEE Conference on Decision and Control
    PublisherIEEE
    Pages2615-2620
    Volume3
    ISBN (Print)0-7803-6638-7
    DOIs
    Publication statusPublished - 1 Dec 2000
    Event39th IEEE Conference on Decision and Control - Sydney, Australia
    Duration: 12 Dec 200015 Dec 2000

    Publication series

    NameIEEE Conference on Decision and Control
    PublisherIEEE
    ISSN (Print)0191-2216

    Conference

    Conference39th IEEE Conference on Decision and Control
    Country/TerritoryAustralia
    CitySydney
    Period12/12/0015/12/00

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