A Recognition Technology of Transmission Lines Conductor Break and Surface Damage
In order to find out the potential strands break and damage faults and prevent its further deterioration, a recognition method of conductor break and surface defects in transmission lines′ unmanned aerial vehicle (UAV) inspection is presented in this paper. First, a conductor image is obtained by th...
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| Format: | Article |
| Language: | Chinese |
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Harbin University of Science and Technology Publications
2022-04-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2130 |
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| author | ZENG Jun ZHAO Zi-gen LIU Jing-li LIU Hong-jun CAO Lei GENG Shao-bo WAN Hong-yan |
| author_facet | ZENG Jun ZHAO Zi-gen LIU Jing-li LIU Hong-jun CAO Lei GENG Shao-bo WAN Hong-yan |
| author_sort | ZENG Jun |
| collection | DOAJ |
| description | In order to find out the potential strands break and damage faults and prevent its further deterioration, a recognition method of conductor break and surface defects in transmission lines′ unmanned aerial vehicle (UAV) inspection is presented in this paper. First, a conductor image is obtained by the UAV image acquisition system, and then, the conductor region is extracted by the adaptive threshold segmentation after the enhancement processing by the gray variance normalization method (GVN). Second, the conductor break is detected by the square wave transformation (SWT) of its grayscale distribution curves, which is simple and effective. Meanwhile, the conductor surface defects are identified by the projection algorithm of the GVN image of the conductor region. Finally, calculating the number of broken strands and filtering the suspect defects, the final fault diagnosis results can be obtained. We analyze the performance of the technology by a series of experiments, and the results show that the proposed method can measure the conductor break and surface defects faults with the average accuracy of 90.45% and 92.05%, respectively. |
| format | Article |
| id | doaj-art-a01c7d1431e84db9aa8cbc037e69f18c |
| institution | Matheson Library |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2022-04-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-a01c7d1431e84db9aa8cbc037e69f18c2025-08-01T09:35:19ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832022-04-01270212213210.15938/j.jhust.2022.02.016A Recognition Technology of Transmission Lines Conductor Break and Surface DamageZENG Jun0ZHAO Zi-gen1LIU Jing-li2LIU Hong-jun3CAO Lei4GENG Shao-bo5WAN Hong-yan6Baoding Power Supply Company of SGCC, Baoding 071000; 2.CYG SUNRI CO., LTD Shenzhen 518057CYG SUNRI CO., LTD Shenzhen 518057Baoding Power Supply Company of SGCC, Baoding 071000CYG SUNRI CO., LTD Shenzhen 518057Baoding Power Supply Company of SGCC, Baoding 071000State Grid Hebei Electric Power Limited Company, Shijiazhuang 050021Baoding Power Supply Company of SGCC, Baoding 071000In order to find out the potential strands break and damage faults and prevent its further deterioration, a recognition method of conductor break and surface defects in transmission lines′ unmanned aerial vehicle (UAV) inspection is presented in this paper. First, a conductor image is obtained by the UAV image acquisition system, and then, the conductor region is extracted by the adaptive threshold segmentation after the enhancement processing by the gray variance normalization method (GVN). Second, the conductor break is detected by the square wave transformation (SWT) of its grayscale distribution curves, which is simple and effective. Meanwhile, the conductor surface defects are identified by the projection algorithm of the GVN image of the conductor region. Finally, calculating the number of broken strands and filtering the suspect defects, the final fault diagnosis results can be obtained. We analyze the performance of the technology by a series of experiments, and the results show that the proposed method can measure the conductor break and surface defects faults with the average accuracy of 90.45% and 92.05%, respectively.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2130conductor breaksurface defectsimage processingtransmission lines |
| spellingShingle | ZENG Jun ZHAO Zi-gen LIU Jing-li LIU Hong-jun CAO Lei GENG Shao-bo WAN Hong-yan A Recognition Technology of Transmission Lines Conductor Break and Surface Damage Journal of Harbin University of Science and Technology conductor break surface defects image processing transmission lines |
| title | A Recognition Technology of Transmission Lines Conductor Break and Surface Damage |
| title_full | A Recognition Technology of Transmission Lines Conductor Break and Surface Damage |
| title_fullStr | A Recognition Technology of Transmission Lines Conductor Break and Surface Damage |
| title_full_unstemmed | A Recognition Technology of Transmission Lines Conductor Break and Surface Damage |
| title_short | A Recognition Technology of Transmission Lines Conductor Break and Surface Damage |
| title_sort | recognition technology of transmission lines conductor break and surface damage |
| topic | conductor break surface defects image processing transmission lines |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2130 |
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