The invention discloses an insulator identification method for an unmanned aerial vehicle polling an electric transmission line. The method comprises the steps: image collecting and processing: extracting sub-images for training from insulator images of the electric transmission line and initially processing the sub-images to form a training data set; packaging the extracted sub-images for training and adding labels corresponding to the sub-images; training the data by virtue of a convolutional neural network (CNN) algorithm in deep learning to obtain a detection model for insulators; insulator target region detection: detecting an electric transmission line image to obtain a candidate frame of the insulator target; carrying out non-maxima suppression on the candidate frame to obtain a final insulator candidate frame; and carrying out straight line fitting operation on the obtained final insulator candidate frame to obtain a central point and the angle and size information of the candidate frame and finally labeling on the insulator images of the electric transmission line. According to the method disclosed by the invention, images obtained by polling are screened, so that the burden of manual screening is alleviated and the method has a broad application prospect.