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21 June 2024 Research on image recognition technology of overhead transmission line damage
Qianxin Zhu, Ming Fang, Qianjin Wang, Ten Yang, Hongjiang Yin, Yi Zhang, Bingzhen Zhang, Yaoping Wang, Junpeng Dang, Tao Wang
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Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131672C (2024) https://doi.org/10.1117/12.3029825
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China
Abstract
The transmission line conductors are an essential component of power system operation. Due to prolonged exposure to the external environment, these conductors are vulnerable to damage caused by various factors, leading to power system failures that have significant impacts on production and daily life. To monitor the condition of transmission conductors, assess the extent of damage, and ensure stable and safe grid operation, we propose an intelligent wire damage identification technology based on transmission wire damage images. Initially, we apply gray variance normalization and median filtering techniques to enhance the quality of the transmission wire image. Subsequently, local threshold segmentation is performed on the enhanced image to extract the wire area. Leveraging the characteristic that damaged areas exhibit higher gray values compared to other regions, we employ a gray value vertical and horizontal projection algorithm along with subsequent filtering processes for identifying surface damages on wires. This approach effectively transforms wire damage recognition into a data processing problem. Finally, through a series of experiments conducted in power maintenance operations, we validate its feasibility.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Qianxin Zhu, Ming Fang, Qianjin Wang, Ten Yang, Hongjiang Yin, Yi Zhang, Bingzhen Zhang, Yaoping Wang, Junpeng Dang, and Tao Wang "Research on image recognition technology of overhead transmission line damage", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131672C (21 June 2024); https://doi.org/10.1117/12.3029825
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KEYWORDS
Image processing
Image segmentation
Image transmission
Detection and tracking algorithms
Tunable filters
Inspection
Image enhancement
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