An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis

The abnormality of electrical equipment will occur when its internal temperature reached beyond its limits, which can lead to subsequent failure of the equipment. Therefore, early prevention is required in order to avoid this fault while maintaining the reliability of the equipment. This research pr...

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Main Author:	Jadin, Mohd Shawal
Format:	Thesis
Language:	English
Published:	2018
Subjects:	T Technology
Online Access:	http://eprints.usm.my/47439/1/An%20Improved%20Framework%20Of%20Region%20Segmentation%20For%20Diagnosing%20Thermal%20Condition%20Of%20Electrical%20Installation%20Based%20On%20Infrared%20Image%20Analysis.pdf
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spelling	my-usm-ep.474392021-11-17T03:42:13Z An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis 2018-07-01 Jadin, Mohd Shawal T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering The abnormality of electrical equipment will occur when its internal temperature reached beyond its limits, which can lead to subsequent failure of the equipment. Therefore, early prevention is required in order to avoid this fault while maintaining the reliability of the equipment. This research proposes a new framework of region segmentation and thermal fault detection method for diagnosing the thermal condition of electrical installation by considering both qualitative and quantitative infrared image analysis. Since most of the electrical installations are normally fixed repetitively, a new region detection method is proposed that is able to detect all identical structure of electrical devices within an infrared image. The method employs the combination of the scale invariant feature transform (SIFT) and maximally stable extremal regions (MSER) keypoint detectors for improving the number of keypoint detection. A method for matching and translating clusters is presented by introducing a voting procedure for finding a group of matched clusters. The region detection is achieved by employing a grid approach to divide the repeated cluster before properly segmenting the target region. For evaluating the condition of electrical installation, the effectiveness of thirteen types of input features is investigated. A wrapper model approach is utilized for selecting feature where the multilayer perceptron (MLP) artificial neural network and the support vector machine (SVM) are used to evaluate each of the possible combinations of the feature set. Based on experimental results on the proposed segmentation method, about 94.27 % of the regions were correctly detected with the average area under curve (AUC) value of 0.79 was achieved. Meanwhile, for assessing the thermal condition, it was found that the integration of Tdelta, Tskew, Tkurt, Tσ and dB features yield the best result when classified by SVM using radial basis kernel function. The highest classification rates are achieved at 99.46% and 97.78% of the accuracy and f-score value, respectively. 2018-07 Thesis http://eprints.usm.my/47439/ http://eprints.usm.my/47439/1/An%20Improved%20Framework%20Of%20Region%20Segmentation%20For%20Diagnosing%20Thermal%20Condition%20Of%20Electrical%20Installation%20Based%20On%20Infrared%20Image%20Analysis.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology Jadin, Mohd Shawal An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
description	The abnormality of electrical equipment will occur when its internal temperature reached beyond its limits, which can lead to subsequent failure of the equipment. Therefore, early prevention is required in order to avoid this fault while maintaining the reliability of the equipment. This research proposes a new framework of region segmentation and thermal fault detection method for diagnosing the thermal condition of electrical installation by considering both qualitative and quantitative infrared image analysis. Since most of the electrical installations are normally fixed repetitively, a new region detection method is proposed that is able to detect all identical structure of electrical devices within an infrared image. The method employs the combination of the scale invariant feature transform (SIFT) and maximally stable extremal regions (MSER) keypoint detectors for improving the number of keypoint detection. A method for matching and translating clusters is presented by introducing a voting procedure for finding a group of matched clusters. The region detection is achieved by employing a grid approach to divide the repeated cluster before properly segmenting the target region. For evaluating the condition of electrical installation, the effectiveness of thirteen types of input features is investigated. A wrapper model approach is utilized for selecting feature where the multilayer perceptron (MLP) artificial neural network and the support vector machine (SVM) are used to evaluate each of the possible combinations of the feature set. Based on experimental results on the proposed segmentation method, about 94.27 % of the regions were correctly detected with the average area under curve (AUC) value of 0.79 was achieved. Meanwhile, for assessing the thermal condition, it was found that the integration of Tdelta, Tskew, Tkurt, Tσ and dB features yield the best result when classified by SVM using radial basis kernel function. The highest classification rates are achieved at 99.46% and 97.78% of the accuracy and f-score value, respectively.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Jadin, Mohd Shawal
author_facet	Jadin, Mohd Shawal
author_sort	Jadin, Mohd Shawal
title	An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
title_short	An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
title_full	An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
title_fullStr	An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
title_full_unstemmed	An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis
title_sort	improved framework of region segmentation for diagnosing thermal condition of electrical installation based on infrared image analysis
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2018
url	http://eprints.usm.my/47439/1/An%20Improved%20Framework%20Of%20Region%20Segmentation%20For%20Diagnosing%20Thermal%20Condition%20Of%20Electrical%20Installation%20Based%20On%20Infrared%20Image%20Analysis.pdf
_version_	1747821777735647232

An Improved Framework Of Region Segmentation For Diagnosing Thermal Condition Of Electrical Installation Based On Infrared Image Analysis

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