Obiekt

Tytuł: Advances in model-based fault diagnosis with evolutionary algorithms and neural networks

Autor:

Witczak, Marcin

Data wydania:

2006

Typ zasobu:

artykuł

Współtwórca:

Korbicz, Józef (1951- ) - red.

Podtytuł:

Soft Computing in Control and Fault Diagnosis

Tytuł publikacji grupowej:

AMCS, Volume 16 (2006)

Abstract:

Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analyticaltechniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniquessuch as evolutionary algorithms and neural networks become more and more popular in industrial applications of faultdiagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionaryalgorithms and neural networks to fault diagnosis. ; In particular, a brief introduction to these computational intelligenceparadigms is presented, and then a review of their fault detection and isolation applications is performed. Close attention ispaid to techniques that integrate the classical and soft computing methods. A selected group of them is carefully describedin the paper. The performance of the presented approaches is illustrated with the use of the DAMADICS fault detectionbenchmark that deals with a valve actuator.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Identyfikator zasobu:

oai:zbc.uz.zgora.pl:46823

Strony:

85-99

Źródło:

AMCS, Volume 16, Number 1 (2006) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego

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