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Model-based fault detection and diagnosis optimization for process control rig

One of the challenges research on model based fault detection and diagnosis of a system is finding the accurate models. In this paper, fuzzy logic based model using genetic algorithm for optimizing the membership function is used in the development of fault detection and diagnosis of a process contr...

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Main Authors:	Rahman, R. Z. A., Yusof, R., Ismail, F. S.
Format:	Conference or Workshop Item
Published:	2013
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/51171/ http://dx.doi.org/10.1109/ASCC.2013.6606106
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id	my.utm.51171
record_format	eprints
spelling	my.utm.511712017-09-17T08:11:07Z http://eprints.utm.my/id/eprint/51171/ Model-based fault detection and diagnosis optimization for process control rig Rahman, R. Z. A. Yusof, R. Ismail, F. S. TK Electrical engineering. Electronics Nuclear engineering One of the challenges research on model based fault detection and diagnosis of a system is finding the accurate models. In this paper, fuzzy logic based model using genetic algorithm for optimizing the membership function is used in the development of fault detection and diagnosis of a process control rig. The model is used to generate various residual signals, which relate to the faults of the system. These residual signals are used by artificial neural networks to classify the respective faults and finally to determine the faults of the system. Comparisons of the fault classification technique are done for two different models of the process control rig that are the conventional fuzzy model and the optimized fuzzy-GA model. The results show that the fuzzy-GA model gives more accurate fault classifications as compared to the conventional fuzzy logic model. 2013 Conference or Workshop Item PeerReviewed Rahman, R. Z. A. and Yusof, R. and Ismail, F. S. (2013) Model-based fault detection and diagnosis optimization for process control rig. In: 2013 9Th Asian Control Conference, Ascc 2013. http://dx.doi.org/10.1109/ASCC.2013.6606106
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Rahman, R. Z. A. Yusof, R. Ismail, F. S. Model-based fault detection and diagnosis optimization for process control rig
description	One of the challenges research on model based fault detection and diagnosis of a system is finding the accurate models. In this paper, fuzzy logic based model using genetic algorithm for optimizing the membership function is used in the development of fault detection and diagnosis of a process control rig. The model is used to generate various residual signals, which relate to the faults of the system. These residual signals are used by artificial neural networks to classify the respective faults and finally to determine the faults of the system. Comparisons of the fault classification technique are done for two different models of the process control rig that are the conventional fuzzy model and the optimized fuzzy-GA model. The results show that the fuzzy-GA model gives more accurate fault classifications as compared to the conventional fuzzy logic model.
format	Conference or Workshop Item
author	Rahman, R. Z. A. Yusof, R. Ismail, F. S.
author_facet	Rahman, R. Z. A. Yusof, R. Ismail, F. S.
author_sort	Rahman, R. Z. A.
title	Model-based fault detection and diagnosis optimization for process control rig
title_short	Model-based fault detection and diagnosis optimization for process control rig
title_full	Model-based fault detection and diagnosis optimization for process control rig
title_fullStr	Model-based fault detection and diagnosis optimization for process control rig
title_full_unstemmed	Model-based fault detection and diagnosis optimization for process control rig
title_sort	model-based fault detection and diagnosis optimization for process control rig
publishDate	2013
url	http://eprints.utm.my/id/eprint/51171/ http://dx.doi.org/10.1109/ASCC.2013.6606106
_version_	1643652960656293888
score	13.211869

Model-based fault detection and diagnosis optimization for process control rig

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