Efficient plant supervision strategy using NN based techniques

Authors:
Ramon Ferreiro Garcia;Jose Luis Calvo Rolle;Francisco Javier Perez Castelo
Affiliations:
ETSNM, Dept Industrial Eng., University of La Coruna;EUP, Dept Industrial Eng., University of La Coruna;EUP, Dept Industrial Eng., University of La Coruna
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Year:
2010

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Abstract

Most of non-linear type one and type two control systems suffers from lack of detectability when model based techniques are applied on FDI (fault detection and isolation) tasks In general, all types of processes suffer from lack of detectability also due to the ambiguity to discriminate the process, sensors and actuators in order to isolate any given fault This work deals with a strategy to detect and isolate faults which include massive neural networks based functional approximation procedures associated to recursive rule based techniques applied to a parity space approach.