Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection
Insulators are important safety devices on high-voltage transmission lines. An insulator inspection system based on UAVs is widely used. Insulator defect detection is performed against two main engineering problems: 1. The scarcity of defect images, which leads to a network overfitting problem. 2. T...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/13/6/276 |
| _version_ | 1797486262717775872 |
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| author | Lei Pan Lan Chen Shengli Zhu Wenyan Tong Like Guo |
| author_facet | Lei Pan Lan Chen Shengli Zhu Wenyan Tong Like Guo |
| author_sort | Lei Pan |
| collection | DOAJ |
| description | Insulators are important safety devices on high-voltage transmission lines. An insulator inspection system based on UAVs is widely used. Insulator defect detection is performed against two main engineering problems: 1. The scarcity of defect images, which leads to a network overfitting problem. 2. The small object detection, which is caused by the long aerial photography distance, and the low resolution of the insulator defect area pictures. In this study, firstly, the super-resolution reconstruction method is used to augment the dataset, which can not only solve the overfitting problem but also enrich the image texture features and pixel values of defect areas. Secondly, in the process of insulator defect detection, a two-stage cascading method is used. In the first stage, the rotated object detection algorithm is used to realize the object location of insulator strings, and then images of the identified insulators are cropped to reduce the proportion of the background area in defect images. In the second stage, YOLO v5 is used for the detection of insulator caps that are missing defects. The method proposed shows good detection effect on the self-built training set which contains only 85 images captured from real inspection environments. The method has practical industrial application value. |
| first_indexed | 2024-03-09T23:30:45Z |
| format | Article |
| id | doaj.art-f55b631e9a564e1cb254c22ea5399acb |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-09T23:30:45Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-f55b631e9a564e1cb254c22ea5399acb2023-11-23T17:09:39ZengMDPI AGInformation2078-24892022-05-0113627610.3390/info13060276Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect DetectionLei Pan0Lan Chen1Shengli Zhu2Wenyan Tong3Like Guo4Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, ChinaInstitute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, ChinaBeijing Ikingtec Intelligent Technology Co., Ltd., Beijing 100190, ChinaLiaoning Industry and Trade School, Shenyang 110044, ChinaShenyang Rural Commercial Bank Company Limited, Shenyang110032, ChinaInsulators are important safety devices on high-voltage transmission lines. An insulator inspection system based on UAVs is widely used. Insulator defect detection is performed against two main engineering problems: 1. The scarcity of defect images, which leads to a network overfitting problem. 2. The small object detection, which is caused by the long aerial photography distance, and the low resolution of the insulator defect area pictures. In this study, firstly, the super-resolution reconstruction method is used to augment the dataset, which can not only solve the overfitting problem but also enrich the image texture features and pixel values of defect areas. Secondly, in the process of insulator defect detection, a two-stage cascading method is used. In the first stage, the rotated object detection algorithm is used to realize the object location of insulator strings, and then images of the identified insulators are cropped to reduce the proportion of the background area in defect images. In the second stage, YOLO v5 is used for the detection of insulator caps that are missing defects. The method proposed shows good detection effect on the self-built training set which contains only 85 images captured from real inspection environments. The method has practical industrial application value.https://www.mdpi.com/2078-2489/13/6/276rotated object detectionSRGANKLD algorithminsulators |
| spellingShingle | Lei Pan Lan Chen Shengli Zhu Wenyan Tong Like Guo Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection Information rotated object detection SRGAN KLD algorithm insulators |
| title | Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection |
| title_full | Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection |
| title_fullStr | Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection |
| title_full_unstemmed | Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection |
| title_short | Research on Small Sample Data-Driven Inspection Technology of UAV for Transmission Line Insulator Defect Detection |
| title_sort | research on small sample data driven inspection technology of uav for transmission line insulator defect detection |
| topic | rotated object detection SRGAN KLD algorithm insulators |
| url | https://www.mdpi.com/2078-2489/13/6/276 |
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