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Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant

Any plant, in fact, is combined of many items and systems undergoing processes to come out with output. If the plant is manufacturing plant, the output, then, is production. Thermal power plants are a complex and highly reliable special combination of systems to produce power. With expert knowledge,...

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Main Authors:	Al-Neami, F. B., Al-Kayiem, Hussain H.
Format:	Conference or Workshop Item
Published:	2008
Subjects:	TJ Mechanical engineering and machinery TP Chemical technology
Online Access:	http://eprints.utp.edu.my/4195/1/Firas_NPC08_paper_1_page_.pdf http://eprints.utp.edu.my/4195/
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id	my.utp.eprints.4195
record_format	eprints
spelling	my.utp.eprints.41952017-01-19T08:26:16Z Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant Al-Neami, F. B. Al-Kayiem, Hussain H. TJ Mechanical engineering and machinery TP Chemical technology Any plant, in fact, is combined of many items and systems undergoing processes to come out with output. If the plant is manufacturing plant, the output, then, is production. Thermal power plants are a complex and highly reliable special combination of systems to produce power. With expert knowledge, fault confirmation in the thermal power plants can be prevented by illusive and real- time signals manipulation. The recent work presents a new method of fault diagnosis based on artificial neural networks and genetic algorithms. The networking is under development to resolve this problem. The proposed fault diagnosis method combines ANNs, GAs and classical probability with an expert knowledge base. By assessing the state of the thermal power plant, the ANNs and GAs colonies undergoes a transformation that produces an individual adapted the plant conditions. Results from a preliminary case study are presented by applying the ANNs on a small chemical plant. Keywords: Fault Detection, Thermal Power Plant, Neural Networks (ANNs), Genetic Algorithms (GAs). Intelligent Networking. 2008-04-01 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/4195/1/Firas_NPC08_paper_1_page_.pdf Al-Neami, F. B. and Al-Kayiem, Hussain H. (2008) Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant. In: 1st National Postgraduate Conference, NPC08, 31March to 1 April, Universiti Teknologi PETRONAS. http://eprints.utp.edu.my/4195/
institution	Universiti Teknologi Petronas
building	UTP Resource Centre
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Petronas
content_source	UTP Institutional Repository
url_provider	http://eprints.utp.edu.my/
topic	TJ Mechanical engineering and machinery TP Chemical technology
spellingShingle	TJ Mechanical engineering and machinery TP Chemical technology Al-Neami, F. B. Al-Kayiem, Hussain H. Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
description	Any plant, in fact, is combined of many items and systems undergoing processes to come out with output. If the plant is manufacturing plant, the output, then, is production. Thermal power plants are a complex and highly reliable special combination of systems to produce power. With expert knowledge, fault confirmation in the thermal power plants can be prevented by illusive and real- time signals manipulation. The recent work presents a new method of fault diagnosis based on artificial neural networks and genetic algorithms. The networking is under development to resolve this problem. The proposed fault diagnosis method combines ANNs, GAs and classical probability with an expert knowledge base. By assessing the state of the thermal power plant, the ANNs and GAs colonies undergoes a transformation that produces an individual adapted the plant conditions. Results from a preliminary case study are presented by applying the ANNs on a small chemical plant. Keywords: Fault Detection, Thermal Power Plant, Neural Networks (ANNs), Genetic Algorithms (GAs). Intelligent Networking.
format	Conference or Workshop Item
author	Al-Neami, F. B. Al-Kayiem, Hussain H.
author_facet	Al-Neami, F. B. Al-Kayiem, Hussain H.
author_sort	Al-Neami, F. B.
title	Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
title_short	Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
title_full	Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
title_fullStr	Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
title_full_unstemmed	Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
title_sort	hybrid neural networks and genetic algorithm for fault detection and diagnosis of a plant
publishDate	2008
url	http://eprints.utp.edu.my/4195/1/Firas_NPC08_paper_1_page_.pdf http://eprints.utp.edu.my/4195/
_version_	1738655324259221504
score	13.222552

Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant

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