Research on Insulator Defect Identification and Detection Based on UAV Paddle Vision

Abstract

UAV flight is a highly autonomous special flight activity, it can be detected in the air, on the ground and any other environment, it has the advantages of high efficiency and safety. UAV has the characteristics of safety and flexibility, and it can replace manual power line inspection and insulator defect detection. This paper mainly realizes the image recognition of insulators through the research on the image defect recognition of aerial insulators, and carries out the insulator defect detection on the image recognition results. The traditional insulator defect detection method is to identify insulator defects through the action of mechanical force using probe emission, and then through a series of complex physical processes to form an electrical signal. But this method can no longer meet the requirements of modern society for aircraft power systems. Therefore, researchers have proposed a higher level and more accurate defect detection method, which is realized by computer technology to detect insulators, so that the possible danger points during flight can be more accurately judged, and this reduces to a certain extent the human factors that cause losses when accidents occur. This paper mainly focuses on the UAV paddle view angle, orientation and other parameters extraction algorithm to study.