bounds detection algorithm for substations that integrates visual perception and RTK positioning is discussed. RTK(real-time kinematic positioning)
?is a carrier phase differential real-time dynamic positioning technology,the positioning accuracy canreach the centimeter level but can only measure?
point coordinates,which cannot obtain the perimeter position information of workers. Theorthogonal deployment of surveillance cameras can theoretically?
make up for this defect,but the inherent deficiencies of 2D vision easilylead to certain 3D positioning errors. To this end,based on the popular lightweight object detection model YOLOv5 in recent years,asubstation out-of-bounds detection algorithm that integrates visual perception and RTK positioning is proposed. Considering that someanchor points need to be set as the registration reference for 2D visual positioning and 3D RTK positioning in the proposed algorithm,weadd the attention module CBAM to the traditional YOLOv5 model to enhance the network’s ability to learn the features of the target area.At the same time,Alpha-IoU is introduced as the bounding box regression loss function to improve the robustness of the model to long-tailed small targets. The experimental results in real applications show that the proposed algorithm not only has high detection accuracy ofout-of-bounds violations,but also has excellent real-time performance,which can meet the practical needs of out-of-bounds detectionin the reconstruction and expansion of substations.