Methods of transmission channel insulator detection based on deep learning model
Liping Lu, Lin Li, Jiangyun Yu, Xinghe Qu, Yin Zhimin · 2022
Using artificial intelligence technology to realize intelligent detection and monitoring of transmission lines is one of the key technologies in the construction of new power system. This paper introduces the target detection of transmission channel based on deep learning method. The deep learning method has the advantages of little influence of super parameters on the results, strong feature extraction ability and strong anti-interference ability. This paper mainly introduces the network framework, including YOLO, SSD, R-FCN, fast R-CNN, etc., and analyses the advantages and disadvantages of various methods. At the same time, the transmission channel insulator detection is verified for various network architectures, and the experiments show the applicability of various types to transmission channel target detection.