Traditional method of insulator defect identification is manually operated, which has low efficiency and high cost. Therefore, an automatic method of insulator defect identification is proposed in this paper. Firstly, image segmentation was operated by classification method of Random Forest (RF) to realize the object recognition of the insulator. Then, the method of Convolutional Neural Network (CNN) was adopted to classify the normal and defect states of insulators, and finally, the location of self-explosion defect identification was realized by Faster Region-Convolutional Neural Network (Faster R-CNN). A large number of images of insulators taken by Unmanned Aerial Vehicle (UAV) were used as experimental data to verify the method. The results show that the method in this paper could efficiently identify the defects of insulators, and the recognition rate reached 89.0%. The results can provide some references for the research of insulator defect identification of transmission lines.

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In the transmission system, the continuous load operation and the external environment will make the equipment fault hidden danger, which will affect the stable operation of the transmission system. In this paper, an edge intelligent analysis system of transmission equipment defect image recognition is proposed. The system migrates the cloud image recognition to the edge. Feature Pyramid Network(FPN) is introduced into Single Shot MultiBox Detector(SSD) object detection algorithm based on MobileNet v1 feature extraction network to detect defects of different sizes in large-size, small-size, tower and insulator equipment. So as to realize the rapid positioning of defects and upload the results to the cloud. The results of system application show that the accuracy and recall rate of the proposed system are high. In the case of ensuring the detection accuracy, it meets the real-time requirements of detection. The system can effectively improve the automation level of transmission equipment operation and maintenance. While improving the operation and maintenance efficiency of transmission lines, the safe operation of the transmission system is ensured.