A Review of Transmission Line Defect Detection Based on Deep Learning Object Detection Techniques

With the advantages of easy-to-carry, simple operation, rapid response, and low environmental requirements, UAVs have become increasingly prevalent in the aerial inspection of transmission lines. Central to this aerial inspection is target detection technology, a critical facet whose research profoundly impacts the utility of UAVs. This paper delineates the prevalent defect types in critical transmission line components. Secondly, it combs through the research status of defect detection algorithms, focusing on the research progress of deep learning in transmission line defect detection. Then it elaborates on the model selection and practical application of transmission line defect detection methods based on deep learning, and at the same time, it summarizes the application scenarios, results, strengths and weaknesses, and limitations of the defect detection algorithms of transmission lines. Finally, from a practical point of view, it discusses the improvement measures and directions for transmission line defect detection in different backgrounds, points out the current difficulties, and looks forward to the trend of future development.