Review on online operation insulator identification and fault diagnosis based on UAV patrol images and deep learning algorithms

Abstract

Artificial intelligence has great potential for use in smart grids. Power system image recognition based on artificial intelligence is an important research direction. The insulator is essential equipment for the power grid and is related to operational safety. Online operating insulator location identification and fault diagnosis technologies based on unmanned aerial vehicle (UAV) patrol the images, and deep learning algorithms have been continuously suggested and developed. These technologies have achieved good results in practical application. By compiling the recent literature on insulator detection technology, three common application scenarios and research difficulties are uncovered: The need for increased detection accuracy and real-time speed; faulty image recognition of complex backgrounds and target occlusion; and multiscale object and small object detection improvements. At the same time, the improved algorithms in the literature are comprehensively summarized, and the performance evaluation indices of various algorithms are compared.