UAV (Unmanned Aerial Vehicle) inspection is one of the main ways of transmission line inspection, which plays an important role in ensuring the transmission safety. In view of the disadvantages of existing inspection methods, such as slow detection speed, large calculation of detection model, and inability to adapt to low light environment, an improved algorithm based on YOLO (You Only Look Once) v3 is proposed to realize the real-time detection of power towers and insulators. First of all, a data set of power towers and insulators is established, which are inverted and transformed to expand the data volume. Secondly, the network structure of YOLO v3 is simplified and the calculation of the detection model is reduced. Res unit is added to reuse convolution feature. Then, K-means is used to cluster the new data set to get more accurate anchor value, which improves the detection accuracy. Through the experimental demonstration, the accuracy of the proposed scheme for the detection of key parts of the transmission line is 4% higher than the original YOLO, and the detection speed reaches 33.6 ms/frame.