Research on data augmentation method of transmission line based on edge guidance
CHEN Yonghua
LIANG Qishuai
ZHAO Kai
ZENG Zhuangdong
DUAN Fuxiu
FU Shubo
Abstract：In the modern power system,the inspection and maintenance of transmission lines is a key link to ensure the safe and stable operation of the power grid.With the development of drone technology,the use of drones for transmission line inspection has become an efficient and economical method.Under severe weather conditions such as rainy days,the image quality of transmission lines taken by UAVs is seriously affected,which brings difficulties to subsequent fault detection and analysis.In order to solve this problem,this paper proposes a transmission line data augmentation method based on edge guidance.Firstly,the multidirectional Sobel operator and Laplace operator are used to extract the features of the transmission line image under rainy conditions,which can effectively capture the edge information in the image,especially the significant edge of the transmission line.The extracted features are applied to the deep learning network,and the network model is trained to realize the restoration and enhancement of the transmission line image in rainy days.The results show that the proposed method can significantly improve the quality of transmission line images in rainy days,and provide more reliable data support for subsequent fault detection and analysis.
Keywords：transmission line image enhancementedge guidanceedge operatorsdeep learning
Publication Date：2025-07-31
Pages：6( 54-59 )