Optimization method of transmission line UAV inspection path based on ant colony algorithm

Abstract

The present invention relates to a method for optimizing transmission line UAV patrol inspection path based on ant colony algorithm, including: obtaining geographical information data of transmission line and tower; obtaining inspection UAV parameters, tower physical data and wireless network coverage area; Mark in the satellite map image, and mark the contour line in the satellite map image; calculate the effective link distance of the UAV and the minimum altitude of the tower inspection task point; draw the UAV inspection in the satellite map image effective link area; superimpose the wireless network coverage area, tower marking and effective link area of ​​UAV inspection on the road map, and set the take-off and landing points of inspection UAV; establish transmission line UAV inspection Inspection path planning model; solve to obtain the optimal UAV inspection path set. The invention uses an artificial intelligence algorithm to obtain the optimal set of inspection paths of the drone, which greatly improves the inspection efficiency of the transmission line and effectively ensures the safe and stable operation of the power grid.

Description

Optimization method of UAV inspection path for transmission line based on ant colony algorithm technical field The invention belongs to the transmission line maintenance field, be specifically related to a kind of transmission line unmanned aerial vehicle patrolling based on ant colony algorithm Check the path optimization method. Background technique [0002] After the rapid development in the power industry in recent years, unmanned aerial vehicles have been widely used in fine In the work of chemical inspection, prevention of external force damage, and prevention of mountain fires. The refined inspection of UAVs uses multi-rotor UAVs, based on power lines Road high-precision 3D point cloud, planning a refined inspection route for all components of the tower, and realizing the full autonomy of the UAV on the tower mission flight. Since refined inspection requires extremely high spatial positioning, most UAV inspection tasks use network RTK. technology to meet the...

AI Technical Summary

Problems solved by technology

When performing refined inspection tasks, UAVs are often limited by factors such as network coverage, terrain occlusion, battery life, and ultra-long distance. It is difficult to quickly find a suitable UAV take-off and landing point, which greatly affects the efficiency of inspections. , and safety accidents frequently occur during inspection mission flights

In the face of complex topography and complex transmission line energy network, the existing large-scale attempts based on manual inspection experience and manual labeling of maps can no longer meet the requirements for the selection of take-off and landing points for various types of UAV operations.

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