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Proceedings Paper

Fault detection and isolation using a neofuzzy neuron-based system
Author(s): Darcy Novoa-Paredes; Francklin Rivas-Echeverria; Cesar Bravo-Bravo
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Paper Abstract

In this paper a fault detection and isolation scheme using a set of Neo fuzzy neurons will be presented. Such neurons use IF-THEN rules for characterizing the synaptic junctions in order to obtain complex nonlinear input/output maps in a simple structure, allowing an improvement of the learning and representation capabilities. As illustrative example, the fault detection scheme in a three interconnected tank system will be presented.

Paper Details

Date Published: 21 March 2001
PDF: 9 pages
Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); doi: 10.1117/12.421161
Show Author Affiliations
Darcy Novoa-Paredes, Univ. de Los Andes (Venezuela)
Francklin Rivas-Echeverria, Univ. de Los Andes (Venezuela)
Cesar Bravo-Bravo, Univ. de Los Andes (Venezuela)

Published in SPIE Proceedings Vol. 4390:
Applications and Science of Computational Intelligence IV
Kevin L. Priddy; Paul E. Keller; Peter J. Angeline, Editor(s)

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