Research on insulator defect detection algorithm of transmission line based on CenterNet.

The reliability of the insulator has directly affected the stable operation of electric power system. The detection of defective insulators has always been an important issue in smart grid systems. However, the traditional transmission line detection method has low accuracy and poor real-time perfor...

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Autores principales:	Chunming Wu, Xin Ma, Xiangxu Kong, Haichao Zhu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/885f133d575e4021a9d31938e1d358dd
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id	oai:doaj.org-article:885f133d575e4021a9d31938e1d358dd
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spelling	oai:doaj.org-article:885f133d575e4021a9d31938e1d358dd2021-12-02T20:08:55ZResearch on insulator defect detection algorithm of transmission line based on CenterNet.1932-620310.1371/journal.pone.0255135https://doaj.org/article/885f133d575e4021a9d31938e1d358dd2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255135https://doaj.org/toc/1932-6203The reliability of the insulator has directly affected the stable operation of electric power system. The detection of defective insulators has always been an important issue in smart grid systems. However, the traditional transmission line detection method has low accuracy and poor real-time performance. We present an insulator defect detection method based on CenterNet. In order to improve detection efficiency, we simplified the backbone network. In addition, an attention mechanism is utilized to suppress useless information and improve the accuracy of network detection. In image preprocessing, the blurring of some detected images results in the samples being discarded, so we use super-resolution reconstruction algorithm to reconstruct the blurred images to enhance the dataset. The results show that the AP of the proposed method reaches 96.16% and the reasoning speed reaches 30FPS under the test condition of NVIDIA GTX 1080 test conditions. Compared with Faster R-CNN, YOLOV3, RetinaNet and FSAF, the detection accuracy of proposed method is greatly improved, which fully proves the effectiveness of the proposed method.Chunming WuXin MaXiangxu KongHaichao ZhuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0255135 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chunming Wu Xin Ma Xiangxu Kong Haichao Zhu Research on insulator defect detection algorithm of transmission line based on CenterNet.
description	The reliability of the insulator has directly affected the stable operation of electric power system. The detection of defective insulators has always been an important issue in smart grid systems. However, the traditional transmission line detection method has low accuracy and poor real-time performance. We present an insulator defect detection method based on CenterNet. In order to improve detection efficiency, we simplified the backbone network. In addition, an attention mechanism is utilized to suppress useless information and improve the accuracy of network detection. In image preprocessing, the blurring of some detected images results in the samples being discarded, so we use super-resolution reconstruction algorithm to reconstruct the blurred images to enhance the dataset. The results show that the AP of the proposed method reaches 96.16% and the reasoning speed reaches 30FPS under the test condition of NVIDIA GTX 1080 test conditions. Compared with Faster R-CNN, YOLOV3, RetinaNet and FSAF, the detection accuracy of proposed method is greatly improved, which fully proves the effectiveness of the proposed method.
format	article
author	Chunming Wu Xin Ma Xiangxu Kong Haichao Zhu
author_facet	Chunming Wu Xin Ma Xiangxu Kong Haichao Zhu
author_sort	Chunming Wu
title	Research on insulator defect detection algorithm of transmission line based on CenterNet.
title_short	Research on insulator defect detection algorithm of transmission line based on CenterNet.
title_full	Research on insulator defect detection algorithm of transmission line based on CenterNet.
title_fullStr	Research on insulator defect detection algorithm of transmission line based on CenterNet.
title_full_unstemmed	Research on insulator defect detection algorithm of transmission line based on CenterNet.
title_sort	research on insulator defect detection algorithm of transmission line based on centernet.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/885f133d575e4021a9d31938e1d358dd
work_keys_str_mv	AT chunmingwu researchoninsulatordefectdetectionalgorithmoftransmissionlinebasedoncenternet AT xinma researchoninsulatordefectdetectionalgorithmoftransmissionlinebasedoncenternet AT xiangxukong researchoninsulatordefectdetectionalgorithmoftransmissionlinebasedoncenternet AT haichaozhu researchoninsulatordefectdetectionalgorithmoftransmissionlinebasedoncenternet
_version_	1718375135413534720

Research on insulator defect detection algorithm of transmission line based on CenterNet.

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