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Proceedings Paper

Artificial-neural-network-based failure detection and isolation
Author(s): Mokhtar Sadok; Imed Gharsalli; Ali T. Alouani
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Paper Abstract

This paper presents the design of a systematic failure detection and isolation system that uses the concept of failure sensitive variables (FSV) and artificial neural networks (ANN). The proposed approach was applied to tube leak detection in a utility boiler system. Results of the experimental testing are presented in the paper.

Paper Details

Date Published: 25 March 1998
PDF: 7 pages
Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); doi: 10.1117/12.304808
Show Author Affiliations
Mokhtar Sadok, Tennessee Technological Univ. (United States)
Imed Gharsalli, Tennessee Technological Univ. (United States)
Ali T. Alouani, Tennessee Technological Univ. (United States)

Published in SPIE Proceedings Vol. 3390:
Applications and Science of Computational Intelligence
Steven K. Rogers; David B. Fogel; James C. Bezdek; Bruno Bosacchi, Editor(s)

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