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Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection

The rapid expansion of power transmission infrastructure necessitates the development of efficient and accurate inspection methods. This paper proposes an autonomous positioning model for Unmanned Aerial Vehicles (UAVs) that can detect power line insulators on transmission lines to address this need...

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Main Authors: Sze Sin, Voon, Kho, Lee Chin, Ngu, Sze Song, Annie, Joseph, Kuryati, Kipli
Format: Article
Language:English
Published: Advances in Electrical and Electronic Engineering (AEEE) 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://ir.unimas.my/id/eprint/46252/1/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20For%20Power%20Lines%20Insulator%20Detection.pdf
http://ir.unimas.my/id/eprint/46252/
https://advances.vsb.cz/data/articles/2024/Vol%2022,%20No%203/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20(UAV)%20For%20Power%20Lines%20Insulator%20Detection.pdf
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spelling my.unimas.ir-462522024-10-09T02:02:24Z http://ir.unimas.my/id/eprint/46252/ Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection Sze Sin, Voon Kho, Lee Chin Ngu, Sze Song Annie, Joseph Kuryati, Kipli TK Electrical engineering. Electronics Nuclear engineering The rapid expansion of power transmission infrastructure necessitates the development of efficient and accurate inspection methods. This paper proposes an autonomous positioning model for Unmanned Aerial Vehicles (UAVs) that can detect power line insulators on transmission lines to address this need. The proposed model leverages machine learning algorithms for autonomous detection of insulators. To determine the optimal stopping point and safety distance between the UAV and the insulator, a mathematical model is presented that utilises the captured images and the machine learning algorithm. A simulation model is utilised to verify the proposed model, ensuring that the UAV moves to the best-predicted position. The machine learning algorithms are utilised to identify and calculate the length of power line insulators. A set of labelled insulator images is trained in the selected machine learning algorithm, enabling it to accurately determine the length of insulators in new images. The mathematical model considers the size of the insulator in the image to calculate the safety distance between the UAV and the power line insulator, while also determining the optimal image shooting coordinate. MATLAB’s Simulink software is utilised to leverage the UAV’s navigation and control systems, enabling it to move to the best position for capturing high-quality photos of the power transmission lines. The model also considers environmental conditions and operational constraints for optimisation. The proposed autonomous positioning model has undergone extensive simulation to demonstrate its effectiveness. Furthermore, the autonomous positioning of the UAV reduces human intervention, minimises inspection time, and increases efficiency and cost-effectiveness. Advances in Electrical and Electronic Engineering (AEEE) 2024-09-30 Article PeerReviewed text en http://ir.unimas.my/id/eprint/46252/1/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20For%20Power%20Lines%20Insulator%20Detection.pdf Sze Sin, Voon and Kho, Lee Chin and Ngu, Sze Song and Annie, Joseph and Kuryati, Kipli (2024) Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection. ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING, 22 (3). pp. 250-259. ISSN 1804-3119 https://advances.vsb.cz/data/articles/2024/Vol%2022,%20No%203/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20(UAV)%20For%20Power%20Lines%20Insulator%20Detection.pdf DOI: 10.15598/aeee.v22i3.5526
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Sze Sin, Voon
Kho, Lee Chin
Ngu, Sze Song
Annie, Joseph
Kuryati, Kipli
Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
description The rapid expansion of power transmission infrastructure necessitates the development of efficient and accurate inspection methods. This paper proposes an autonomous positioning model for Unmanned Aerial Vehicles (UAVs) that can detect power line insulators on transmission lines to address this need. The proposed model leverages machine learning algorithms for autonomous detection of insulators. To determine the optimal stopping point and safety distance between the UAV and the insulator, a mathematical model is presented that utilises the captured images and the machine learning algorithm. A simulation model is utilised to verify the proposed model, ensuring that the UAV moves to the best-predicted position. The machine learning algorithms are utilised to identify and calculate the length of power line insulators. A set of labelled insulator images is trained in the selected machine learning algorithm, enabling it to accurately determine the length of insulators in new images. The mathematical model considers the size of the insulator in the image to calculate the safety distance between the UAV and the power line insulator, while also determining the optimal image shooting coordinate. MATLAB’s Simulink software is utilised to leverage the UAV’s navigation and control systems, enabling it to move to the best position for capturing high-quality photos of the power transmission lines. The model also considers environmental conditions and operational constraints for optimisation. The proposed autonomous positioning model has undergone extensive simulation to demonstrate its effectiveness. Furthermore, the autonomous positioning of the UAV reduces human intervention, minimises inspection time, and increases efficiency and cost-effectiveness.
format Article
author Sze Sin, Voon
Kho, Lee Chin
Ngu, Sze Song
Annie, Joseph
Kuryati, Kipli
author_facet Sze Sin, Voon
Kho, Lee Chin
Ngu, Sze Song
Annie, Joseph
Kuryati, Kipli
author_sort Sze Sin, Voon
title Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
title_short Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
title_full Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
title_fullStr Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
title_full_unstemmed Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
title_sort autonomous positioning of unmanned aerial vehicle (uav) for power lines insulator detection
publisher Advances in Electrical and Electronic Engineering (AEEE)
publishDate 2024
url http://ir.unimas.my/id/eprint/46252/1/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20For%20Power%20Lines%20Insulator%20Detection.pdf
http://ir.unimas.my/id/eprint/46252/
https://advances.vsb.cz/data/articles/2024/Vol%2022,%20No%203/Autonomous%20Positioning%20Of%20Unmanned%20Aerial%20Vehicle%20(UAV)%20For%20Power%20Lines%20Insulator%20Detection.pdf
_version_ 1814942140841590784
score 13.211869

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