Human-machine collaborative inspection of transmission corridors based on the BeiDou positioning

Abstract Inadequate inspection performance of transmission lines leads to damages, posing threats to the safety of power grids. To enhance the efficiency of transmission line inspection and to reduce safety hazards, a method based on the BeiDou positioning for human-machine collaboration in transmission line inspection is proposed. Drones equipped with then BeiDou positioning are utilized to collect transmission line data via the Web Mercator projection, determining the inspection routes. Fault parameters of transmission lines are extracted for manual monitoring, identifying overlay current and voltage frequency fault characteristics. The optimal inspection route is then determined based on these features, achieving human-machine collaboration in transmission line inspection. Experimental results demonstrate that the proposed method detected 11 fault nodes, with inspection paths closely matching the transmission line structure. It identified six defects in power system transmission lines, with an inspection time of only 2.3 seconds. The area under the ROC curve, encompassing true positive and false positive rates, is approximately 5000, indicating the method’s effectiveness, efficiency, and accuracy in inspection.