No Cover Image

Journal article 32 views

A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model

Imene Ferrah, Youcef Benmahamed, Hayder Jahanger Orcid Logo, Madjid Teguar, Omar Kherif Orcid Logo

IET Science, Measurement & Technology, Volume: 19, Issue: 1

Swansea University Author: Hayder Jahanger Orcid Logo

  • 69165.VoR.pdf

    PDF | Version of Record

    © 2025 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License.

    Download (2.01MB)

Check full text

DOI (Published version): 10.1049/smt2.70002

Abstract

This study presents an innovative approach to identify electrical discharges by proposing an algorithm incorporating fractal geometry concepts. Based on the box-counting method, our algorithm is developed to detect and track the progression of electrical discharges leading to flashover. This is achi...

Full description

Published in: IET Science, Measurement & Technology
ISSN: 1751-8822 1751-8830
Published: Institution of Engineering and Technology (IET) 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa69165
first_indexed 2025-03-28T12:38:01Z
last_indexed 2025-04-09T04:41:13Z
id cronfa69165
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2025-04-08T15:33:16.6863829</datestamp><bib-version>v2</bib-version><id>69165</id><entry>2025-03-28</entry><title>A New Box&#x2010;Counting&#x2010;Based&#x2010;Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model</title><swanseaauthors><author><sid>c6171aaf3b59c2199c3e5e979b502e3f</sid><ORCID>0000-0002-6366-1960</ORCID><firstname>Hayder</firstname><surname>Jahanger</surname><name>Hayder Jahanger</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2025-03-28</date><deptcode>ACEM</deptcode><abstract>This study presents an innovative approach to identify electrical discharges by proposing an algorithm incorporating fractal geometry concepts. Based on the box-counting method, our algorithm is developed to detect and track the progression of electrical discharges leading to flashover. This is achieved by calculating the fractal dimension of discharge images which are visual representations of electrical activity recorded during experiments on a planar glass insulator model subjected to different levels of contamination. First, the RGB image is transformed into a binary matrix using the NIBLAK binarization algorithm. Subsequently, the acquired matrix is converted into a square matrix, and its fractal dimension is computed for various resolutions. The final fractal dimension of the image is calculated using the least squares method. This latter is applied to the fractal dimensions (FDs) across all resolutions. According to our algorithm, discharge images have FD values ranging from 1.15 to 1.25. FD increases are observed with applied voltage and non-soluble deposit density (NSDD). The density and activity of discharges also increase with FD. Specifically, a discharge is considered &#x201C;no-arc&#x201D; if FD is less than 1.2 and &#x201C;arc&#x201D; otherwise.</abstract><type>Journal Article</type><journal>IET Science, Measurement &amp;amp; Technology</journal><volume>19</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Institution of Engineering and Technology (IET)</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1751-8822</issnPrint><issnElectronic>1751-8830</issnElectronic><keywords>arcing discharge; binarization algorithm; box-counting method; flashover; fractal dimension; insulator pollution; Niblack method</keywords><publishedDay>1</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-12-01</publishedDate><doi>10.1049/smt2.70002</doi><url/><notes/><college>COLLEGE NANME</college><department>Aerospace, Civil, Electrical, and Mechanical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>ACEM</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>Swansea University</funders><projectreference/><lastEdited>2025-04-08T15:33:16.6863829</lastEdited><Created>2025-03-28T12:35:49.8682559</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering</level></path><authors><author><firstname>Imene</firstname><surname>Ferrah</surname><order>1</order></author><author><firstname>Youcef</firstname><surname>Benmahamed</surname><order>2</order></author><author><firstname>Hayder</firstname><surname>Jahanger</surname><orcid>0000-0002-6366-1960</orcid><order>3</order></author><author><firstname>Madjid</firstname><surname>Teguar</surname><order>4</order></author><author><firstname>Omar</firstname><surname>Kherif</surname><orcid>0000-0002-0888-298x</orcid><order>5</order></author></authors><documents><document><filename>69165__33967__8b1465dfdff840dbbc459e18227495e1.pdf</filename><originalFilename>69165.VoR.pdf</originalFilename><uploaded>2025-04-08T15:29:04.2249951</uploaded><type>Output</type><contentLength>2106811</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2025 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2025-04-08T15:33:16.6863829 v2 69165 2025-03-28 A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model c6171aaf3b59c2199c3e5e979b502e3f 0000-0002-6366-1960 Hayder Jahanger Hayder Jahanger true false 2025-03-28 ACEM This study presents an innovative approach to identify electrical discharges by proposing an algorithm incorporating fractal geometry concepts. Based on the box-counting method, our algorithm is developed to detect and track the progression of electrical discharges leading to flashover. This is achieved by calculating the fractal dimension of discharge images which are visual representations of electrical activity recorded during experiments on a planar glass insulator model subjected to different levels of contamination. First, the RGB image is transformed into a binary matrix using the NIBLAK binarization algorithm. Subsequently, the acquired matrix is converted into a square matrix, and its fractal dimension is computed for various resolutions. The final fractal dimension of the image is calculated using the least squares method. This latter is applied to the fractal dimensions (FDs) across all resolutions. According to our algorithm, discharge images have FD values ranging from 1.15 to 1.25. FD increases are observed with applied voltage and non-soluble deposit density (NSDD). The density and activity of discharges also increase with FD. Specifically, a discharge is considered “no-arc” if FD is less than 1.2 and “arc” otherwise. Journal Article IET Science, Measurement &amp; Technology 19 1 Institution of Engineering and Technology (IET) 1751-8822 1751-8830 arcing discharge; binarization algorithm; box-counting method; flashover; fractal dimension; insulator pollution; Niblack method 1 12 2025 2025-12-01 10.1049/smt2.70002 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2025-04-08T15:33:16.6863829 2025-03-28T12:35:49.8682559 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Imene Ferrah 1 Youcef Benmahamed 2 Hayder Jahanger 0000-0002-6366-1960 3 Madjid Teguar 4 Omar Kherif 0000-0002-0888-298x 5 69165__33967__8b1465dfdff840dbbc459e18227495e1.pdf 69165.VoR.pdf 2025-04-08T15:29:04.2249951 Output 2106811 application/pdf Version of Record true © 2025 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
spellingShingle A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
Hayder Jahanger
title_short A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
title_full A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
title_fullStr A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
title_full_unstemmed A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
title_sort A New Box‐Counting‐Based‐Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model
author_id_str_mv c6171aaf3b59c2199c3e5e979b502e3f
author_id_fullname_str_mv c6171aaf3b59c2199c3e5e979b502e3f_***_Hayder Jahanger
author Hayder Jahanger
author2 Imene Ferrah
Youcef Benmahamed
Hayder Jahanger
Madjid Teguar
Omar Kherif
format Journal article
container_title IET Science, Measurement &amp; Technology
container_volume 19
container_issue 1
publishDate 2025
institution Swansea University
issn 1751-8822
1751-8830
doi_str_mv 10.1049/smt2.70002
publisher Institution of Engineering and Technology (IET)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
document_store_str 1
active_str 0
description This study presents an innovative approach to identify electrical discharges by proposing an algorithm incorporating fractal geometry concepts. Based on the box-counting method, our algorithm is developed to detect and track the progression of electrical discharges leading to flashover. This is achieved by calculating the fractal dimension of discharge images which are visual representations of electrical activity recorded during experiments on a planar glass insulator model subjected to different levels of contamination. First, the RGB image is transformed into a binary matrix using the NIBLAK binarization algorithm. Subsequently, the acquired matrix is converted into a square matrix, and its fractal dimension is computed for various resolutions. The final fractal dimension of the image is calculated using the least squares method. This latter is applied to the fractal dimensions (FDs) across all resolutions. According to our algorithm, discharge images have FD values ranging from 1.15 to 1.25. FD increases are observed with applied voltage and non-soluble deposit density (NSDD). The density and activity of discharges also increase with FD. Specifically, a discharge is considered “no-arc” if FD is less than 1.2 and “arc” otherwise.
published_date 2025-12-01T08:14:17Z
_version_ 1829180075410456576
score 11.057796

Similar Items