Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot
Efficient and accurate state detection of transmission cables is an important means to ensure reliable transmission. Aiming to realize fast and efficient transmission cable state analysis with the help of a binocular vision tool on a loop dismantling robot, this paper proposes a transmission cable s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2023/7747194 |
| _version_ | 1797871844576985088 |
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| author | Zheng Lu Jiazhen Duan Xiaoqiang Chen Yang Chen |
| author_facet | Zheng Lu Jiazhen Duan Xiaoqiang Chen Yang Chen |
| author_sort | Zheng Lu |
| collection | DOAJ |
| description | Efficient and accurate state detection of transmission cables is an important means to ensure reliable transmission. Aiming to realize fast and efficient transmission cable state analysis with the help of a binocular vision tool on a loop dismantling robot, this paper proposes a transmission cable state recognition method combining motion control and image segmentation technology. In this method, the fuzzy PID control method is adopted to ensure that the wire removal robot can realize high-precision and rapid response control and effectively improve the collection quality of the cable image sample set. Meanwhile, aiming to achieve faster and more efficient data acquisition and state analysis, the state analysis model is sunk to the edge side, and the cable state detection and recognition model is constructed based on the fast RCNN model at the edge of the network to realize the in-depth extraction of feature information, enhance the transmission cable state recognition effect of the state detection model, and improve the response analysis speed of the model. The simulation results show that the accuracy of the proposed method is 97.54%, and its calculation time is 1.034 s, which can effectively realize the analysis and research of transmission cable state under complex working conditions. |
| first_indexed | 2024-04-10T00:50:29Z |
| format | Article |
| id | doaj.art-25420d9f6b3d46a2a074ec7c5dfa84a6 |
| institution | Directory Open Access Journal |
| issn | 1687-9619 |
| language | English |
| last_indexed | 2024-04-10T00:50:29Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj.art-25420d9f6b3d46a2a074ec7c5dfa84a62023-03-13T11:25:37ZengHindawi LimitedJournal of Robotics1687-96192023-01-01202310.1155/2023/7747194Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing RobotZheng Lu0Jiazhen Duan1Xiaoqiang Chen2Yang Chen3Changzhou Jinling Electric Power Industrial Co., Ltd.Transmission and Distribution Engineering CompanyState Grid Changzhou Power Supply CompanySchool of Microelectronics and Control EngineeringEfficient and accurate state detection of transmission cables is an important means to ensure reliable transmission. Aiming to realize fast and efficient transmission cable state analysis with the help of a binocular vision tool on a loop dismantling robot, this paper proposes a transmission cable state recognition method combining motion control and image segmentation technology. In this method, the fuzzy PID control method is adopted to ensure that the wire removal robot can realize high-precision and rapid response control and effectively improve the collection quality of the cable image sample set. Meanwhile, aiming to achieve faster and more efficient data acquisition and state analysis, the state analysis model is sunk to the edge side, and the cable state detection and recognition model is constructed based on the fast RCNN model at the edge of the network to realize the in-depth extraction of feature information, enhance the transmission cable state recognition effect of the state detection model, and improve the response analysis speed of the model. The simulation results show that the accuracy of the proposed method is 97.54%, and its calculation time is 1.034 s, which can effectively realize the analysis and research of transmission cable state under complex working conditions.http://dx.doi.org/10.1155/2023/7747194 |
| spellingShingle | Zheng Lu Jiazhen Duan Xiaoqiang Chen Yang Chen Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot Journal of Robotics |
| title | Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot |
| title_full | Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot |
| title_fullStr | Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot |
| title_full_unstemmed | Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot |
| title_short | Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot |
| title_sort | transmission line condition monitoring method based on binocular vision and edge computing for line changing robot |
| url | http://dx.doi.org/10.1155/2023/7747194 |
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