基于深度学习的架空输电线附属障碍物识别研究OA

The overhead line patrol robot plays an important role in improving the line maintenance efficiency and ensuring the safe and stable operation of power system.Aiming at the problem that the overhead line patrol robot needs to effectively identify affiliated obstacles and adopt corresponding obstacle-avoidance actions,this paper stud-ies the deep learning-based affiliated obstacle identification method of overhead transmission line for patrol robots.The overall structure of overhead line patrol robot based on deep learning is discussed.The YOLOv8(you only look once version 8)model and its application in obstacle identification are analyzed based on the overall structure.Fur-thermore,the effectiveness of the proposed method is verified using an augmented obstacle dataset of overhead line.Experimental results show that the proposed overhead line obstacle recognition method has a faster recognition speed and a higher recognition rate,which can meet the obstacle avoidance needs of patrol robots.