Insulator Intelligent Recognition Based on Machine Vision and Edge Calculation
Yuntao Sun, Yong Zhang, Suhong Chen, Yufeng Chen, Chaowei Jin, Shenghui Wang, Fangcheng Lv · 2020 IEEE 3rd Student Conference on Electrical Machines and Systems (SCEMS) · 2020
Insulator is one of the most widely used components in the power grid. Identifing and locating insulator accurately and efficiently is the basis of intelligent evaluation of insulator defects based on UV imaging. The traditional insulator identification and location is mostly done by the back-end server, which has poor real-time performance. Based on this, this paper proposes an insulator intelligent recognition method based on machine vision and edge calculation, builds an edge calculation platform and loads the labeled insulator data set into SSD model for training. The accuracy of recognition is 91.46% and the model file is transplanted to the edge device. At the same time, the edge equipment is equipped with a visual sensor, which can identify the real-time video stream of the insulator. It has a good real-time performance and provides a new scheme for the fault detection of the external insulation equipment.