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Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography

Infrared thermography technology is currently being used in various applications, including fault diagnosis in electrical equipment. Thermal abnormalities are diagnosed by identifying and classifying the hotspot conditions of electrical components. In this article, a new recursively constructed outp...

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Main Authors:	Ahmed, M.M., Huda, A.S.N., Isa, N.A.M.
Format:	Article
Language:	English
Published:	Engineering Applications of Artificial Intelligence 2015
Subjects:	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.um.edu.my/13767/1/Recursive_construction_of_output-context_fuzzy_systems_for_the.pdf http://eprints.um.edu.my/13767/ http://www.sciencedirect.com/science/article/pii/S0952197614002826
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spelling	my.um.eprints.137672015-07-23T00:47:52Z http://eprints.um.edu.my/13767/ Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography Ahmed, M.M. Huda, A.S.N. Isa, N.A.M. T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Infrared thermography technology is currently being used in various applications, including fault diagnosis in electrical equipment. Thermal abnormalities are diagnosed by identifying and classifying the hotspot conditions of electrical components. In this article, a new recursively constructed output-context fuzzy system is proposed to characterize the condition of electrical hotspots. An infrared camera is initially used to capture the thermal images of components with hotspots, and intensity features are extracted from each hotspot. The Recursively Constructed Fuzzy System (RCFS) is then applied to automatically realize and formulate the conditions of the thermal abnormalities. On the basis of the priority level, the hotspot conditions are categorized as normal, warning, and critical. From these three categories, the conditions can be further simplified into two categories, namely, defect (warning and critical) and normal. The proposed RCFS realizes the prominent distinctions in the output domain by using a self-organizing method. The termination of the recursive algorithm finds an effective rule base to achieve an accurate representation of the datasets. The proposed system obtains less fuzzy rules with reasonable accuracy. Our survey of 253 detected regions shows that the proposed RCFS produces 92.3 and 80 testing accuracies for classifying conditions into two and three classes, respectively. The thermographic diagnostic evaluation shows that the proposed intelligent system automatically identifies the rationally acceptable limits of hotspot conditions. Therefore, the proposed system is suitable for establishing an intelligent defect analysis system. (C) 2014 Elsevier Ltd. All rights reserved. Engineering Applications of Artificial Intelligence 2015-03 Article PeerReviewed application/pdf en http://eprints.um.edu.my/13767/1/Recursive_construction_of_output-context_fuzzy_systems_for_the.pdf Ahmed, M.M. and Huda, A.S.N. and Isa, N.A.M. (2015) Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography. Engineering Applications of Artificial Intelligence, 39. pp. 120-131. ISSN 0952-1976 http://www.sciencedirect.com/science/article/pii/S0952197614002826 DOI 10.1016/j.engappai.2014.11.010
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
language	English
topic	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Ahmed, M.M. Huda, A.S.N. Isa, N.A.M. Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
description	Infrared thermography technology is currently being used in various applications, including fault diagnosis in electrical equipment. Thermal abnormalities are diagnosed by identifying and classifying the hotspot conditions of electrical components. In this article, a new recursively constructed output-context fuzzy system is proposed to characterize the condition of electrical hotspots. An infrared camera is initially used to capture the thermal images of components with hotspots, and intensity features are extracted from each hotspot. The Recursively Constructed Fuzzy System (RCFS) is then applied to automatically realize and formulate the conditions of the thermal abnormalities. On the basis of the priority level, the hotspot conditions are categorized as normal, warning, and critical. From these three categories, the conditions can be further simplified into two categories, namely, defect (warning and critical) and normal. The proposed RCFS realizes the prominent distinctions in the output domain by using a self-organizing method. The termination of the recursive algorithm finds an effective rule base to achieve an accurate representation of the datasets. The proposed system obtains less fuzzy rules with reasonable accuracy. Our survey of 253 detected regions shows that the proposed RCFS produces 92.3 and 80 testing accuracies for classifying conditions into two and three classes, respectively. The thermographic diagnostic evaluation shows that the proposed intelligent system automatically identifies the rationally acceptable limits of hotspot conditions. Therefore, the proposed system is suitable for establishing an intelligent defect analysis system. (C) 2014 Elsevier Ltd. All rights reserved.
format	Article
author	Ahmed, M.M. Huda, A.S.N. Isa, N.A.M.
author_facet	Ahmed, M.M. Huda, A.S.N. Isa, N.A.M.
author_sort	Ahmed, M.M.
title	Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
title_short	Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
title_full	Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
title_fullStr	Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
title_full_unstemmed	Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
title_sort	recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography
publisher	Engineering Applications of Artificial Intelligence
publishDate	2015
url	http://eprints.um.edu.my/13767/1/Recursive_construction_of_output-context_fuzzy_systems_for_the.pdf http://eprints.um.edu.my/13767/ http://www.sciencedirect.com/science/article/pii/S0952197614002826
_version_	1643689644096749568
score	13.244745

Recursive construction of output-context fuzzy systems for the condition monitoring of electrical hotspots based on infrared thermography

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