Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8

<p dir="ltr">High voltage electrical infrastructure inspection requires condition monitoring of transmission line assets to avoid any possible failures or emergency. Detection of insulators in strings is linked with electrical infrastructure monitoring pertaining to the insulator fau...

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Main Author: Shafi Muhammad Jiskani (22928323) (author)
Other Authors: Tanweer Hussain (6790679) (author), Anwar Ali Sahito (22928326) (author), Faheemullah Shaikh (20725064) (author), Laveet Kumar (11460088) (author)
Published: 2025
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author Shafi Muhammad Jiskani (22928323)
author2 Tanweer Hussain (6790679)
Anwar Ali Sahito (22928326)
Faheemullah Shaikh (20725064)
Laveet Kumar (11460088)
author2_role author
author
author
author
author_facet Shafi Muhammad Jiskani (22928323)
Tanweer Hussain (6790679)
Anwar Ali Sahito (22928326)
Faheemullah Shaikh (20725064)
Laveet Kumar (11460088)
author_role author
dc.creator.none.fl_str_mv Shafi Muhammad Jiskani (22928323)
Tanweer Hussain (6790679)
Anwar Ali Sahito (22928326)
Faheemullah Shaikh (20725064)
Laveet Kumar (11460088)
dc.date.none.fl_str_mv 2025-08-04T06:00:00Z
dc.identifier.none.fl_str_mv 10.1109/oajpe.2025.3592698
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Electrical_Infrastructure_Monitoring_Case_of_NTDCL_s_500kV_Network_Insulator_Detection_With_YoloV8/30971350
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Electrical engineering
Electronics, sensors and digital hardware
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Condition monitoring
insulator detection
indigenous dataset
NTDCL Pakistan
You Only Look Once (YOLO)
Insulators
Monitoring
Power transmission lines
Accuracy
Autonomous aerial vehicles
Inspection
Deep learning
Poles and towers
dc.title.none.fl_str_mv Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">High voltage electrical infrastructure inspection requires condition monitoring of transmission line assets to avoid any possible failures or emergency. Detection of insulators in strings is linked with electrical infrastructure monitoring pertaining to the insulator fault classification. The dataset widely available for insulator monitoring are either synthetic, lab created or publicly not available. In this paper, an indigenous dataset is created using Autonomous Aerial Vehicles (AAV) technology, capturing images in diverse topographical ambience across different transmission lines/circuits managed by National transmission and dispatch company ltd. in Pakistan. For detection of insulators in string, object detector model You Only Look Once-version 8 (YOLOv8n) is trained on created dataset of 3618 images, 603 being original and other augmented, after preprocessing and augmentation techniques were applied. The model’s performance is up to the mark with accuracy of 92%. The precision and recall being 0.95 and 0.90 respectively, whereas F1 score of the model peaked at 0.95 at confidence level of 0.652.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Open Access Journal of Power and Energy<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/oajpe.2025.3592698" target="_blank">https://dx.doi.org/10.1109/oajpe.2025.3592698</a></p>
eu_rights_str_mv openAccess
id Manara2_0ddac7874bb02f033c901dd2ddcc4d8a
identifier_str_mv 10.1109/oajpe.2025.3592698
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/30971350
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8Shafi Muhammad Jiskani (22928323)Tanweer Hussain (6790679)Anwar Ali Sahito (22928326)Faheemullah Shaikh (20725064)Laveet Kumar (11460088)EngineeringElectrical engineeringElectronics, sensors and digital hardwareInformation and computing sciencesArtificial intelligenceComputer vision and multimedia computationCondition monitoringinsulator detectionindigenous datasetNTDCL PakistanYou Only Look Once (YOLO)InsulatorsMonitoringPower transmission linesAccuracyAutonomous aerial vehiclesInspectionDeep learningPoles and towers<p dir="ltr">High voltage electrical infrastructure inspection requires condition monitoring of transmission line assets to avoid any possible failures or emergency. Detection of insulators in strings is linked with electrical infrastructure monitoring pertaining to the insulator fault classification. The dataset widely available for insulator monitoring are either synthetic, lab created or publicly not available. In this paper, an indigenous dataset is created using Autonomous Aerial Vehicles (AAV) technology, capturing images in diverse topographical ambience across different transmission lines/circuits managed by National transmission and dispatch company ltd. in Pakistan. For detection of insulators in string, object detector model You Only Look Once-version 8 (YOLOv8n) is trained on created dataset of 3618 images, 603 being original and other augmented, after preprocessing and augmentation techniques were applied. The model’s performance is up to the mark with accuracy of 92%. The precision and recall being 0.95 and 0.90 respectively, whereas F1 score of the model peaked at 0.95 at confidence level of 0.652.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Open Access Journal of Power and Energy<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/oajpe.2025.3592698" target="_blank">https://dx.doi.org/10.1109/oajpe.2025.3592698</a></p>2025-08-04T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/oajpe.2025.3592698https://figshare.com/articles/journal_contribution/Electrical_Infrastructure_Monitoring_Case_of_NTDCL_s_500kV_Network_Insulator_Detection_With_YoloV8/30971350CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/309713502025-08-04T06:00:00Z
spellingShingle Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
Shafi Muhammad Jiskani (22928323)
Engineering
Electrical engineering
Electronics, sensors and digital hardware
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Condition monitoring
insulator detection
indigenous dataset
NTDCL Pakistan
You Only Look Once (YOLO)
Insulators
Monitoring
Power transmission lines
Accuracy
Autonomous aerial vehicles
Inspection
Deep learning
Poles and towers
status_str publishedVersion
title Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
title_full Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
title_fullStr Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
title_full_unstemmed Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
title_short Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
title_sort Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
topic Engineering
Electrical engineering
Electronics, sensors and digital hardware
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Condition monitoring
insulator detection
indigenous dataset
NTDCL Pakistan
You Only Look Once (YOLO)
Insulators
Monitoring
Power transmission lines
Accuracy
Autonomous aerial vehicles
Inspection
Deep learning
Poles and towers