Summary of insulator defect detection based on deep learning

Insulator is a kind of key electrical equipment in transmission line. Its long-term operation in strong electric field, high temperature sunshine, mechanical stress, humidity, dirt and other complex environment. This is likely to lead to self-detonation, pollution, flashover and leakage current and other defects, which will reduce insulation performance and seriously affect the safety of power grid. Therefore, power insulator defect detection is an important task in power system detection. How to identify insulator defects quickly and accurately has been an important problem for many scholars. Firstly, this paper reviews the insulator defect detection technology based on traditional detection algorithm. Secondly, the application and key technologies of deep learning algorithm in insulator defect detection are introduced in detail. Then it introduces the challenges and future development trend of this field; Finally, it summarizes this paper and puts forward some suggestions for the development of this field.