Study on Defect Detection Algorithm of Transmission Line in Complex Background
Regular inspection of transmission lines is of great significance to ensure the safe and stable operation of power sys-tems.For the problems of complex background of transmission line aerial images,large changes in target scale and many small targets,a transmission line target detection algorithm based on YOLOv5s is proposed.The algorithm adopts feature refinement module to optimize tiny target features,and embeds SimAM attention module in the network to optimize the feature extraction of the model by means of unified weights of energy functions,and finally introduces NWD loss function to weaken the sensitivity of the model to small target position deviation and improve the recognition and detection ability of the model for small targets.Ex-perimental results show that the average detection accuracy of the model for transmission line targets is as high as 98.8％,which is 1.2％higher compared with the benchmark model.
Transmission line defect detectionAttention mechanismNWD lossFeature refinement
NETL
NSTL
万方数据
