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 proceeding

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
CountryAustralia
CitySydney
Period12/12/0015/12/00

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  • Cite this

    Simani, S., Patton, R. J., Daley, S., & Pike, A. (2000). Identification and fault diagnosis of an industrial gas turbine prototype model. In Proceedings of the 39th IEEE Conference on Decision and Control (Vol. 3, pp. 2615-2620). (IEEE Conference on Decision and Control). IEEE. https://doi.org/10.1109/CDC.2000.914199