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Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines

To address the challenges in the unmanned system-based intelligent inspection of electric transmission line insulators, this paper proposed a multi-geometric reasoning network (MGRN) to accurately detect insulator geometric defects based on aerial images with complex backgrounds and different scales...

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Detalles Bibliográficos
Autores principales: Zhai, Yongjie, Hu, Zhedong, Wang, Qianming, Yang, Qiang, Yang, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416190/
https://www.ncbi.nlm.nih.gov/pubmed/36015863
http://dx.doi.org/10.3390/s22166102
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author Zhai, Yongjie
Hu, Zhedong
Wang, Qianming
Yang, Qiang
Yang, Ke
author_facet Zhai, Yongjie
Hu, Zhedong
Wang, Qianming
Yang, Qiang
Yang, Ke
author_sort Zhai, Yongjie
collection PubMed
description To address the challenges in the unmanned system-based intelligent inspection of electric transmission line insulators, this paper proposed a multi-geometric reasoning network (MGRN) to accurately detect insulator geometric defects based on aerial images with complex backgrounds and different scales. The spatial geometric reasoning sub-module (SGR) was developed to represent the spatial location relationship of defects. The appearance geometric reasoning sub-module (AGR) and the parallel feature transformation (PFT) sub-module were adopted to obtain the appearance geometric features from the real samples. These multi-geometric features can be fused with the original visual features to identify and locate the insulator defects. The proposed solution is assessed through experiments against the existing solutions and the numerical results indicate that it can significantly improve the detection accuracy of multiple insulator defects using the aerial images.
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spelling pubmed-94161902022-08-27 Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines Zhai, Yongjie Hu, Zhedong Wang, Qianming Yang, Qiang Yang, Ke Sensors (Basel) Article To address the challenges in the unmanned system-based intelligent inspection of electric transmission line insulators, this paper proposed a multi-geometric reasoning network (MGRN) to accurately detect insulator geometric defects based on aerial images with complex backgrounds and different scales. The spatial geometric reasoning sub-module (SGR) was developed to represent the spatial location relationship of defects. The appearance geometric reasoning sub-module (AGR) and the parallel feature transformation (PFT) sub-module were adopted to obtain the appearance geometric features from the real samples. These multi-geometric features can be fused with the original visual features to identify and locate the insulator defects. The proposed solution is assessed through experiments against the existing solutions and the numerical results indicate that it can significantly improve the detection accuracy of multiple insulator defects using the aerial images. MDPI 2022-08-15 /pmc/articles/PMC9416190/ /pubmed/36015863 http://dx.doi.org/10.3390/s22166102 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhai, Yongjie
Hu, Zhedong
Wang, Qianming
Yang, Qiang
Yang, Ke
Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title_full Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title_fullStr Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title_full_unstemmed Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title_short Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
title_sort multi-geometric reasoning network for insulator defect detection of electric transmission lines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416190/
https://www.ncbi.nlm.nih.gov/pubmed/36015863
http://dx.doi.org/10.3390/s22166102
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