Abstract
At present, the traditional Unmanned Aerial Vehicle (UAV) power line inspection project mainly uses UAV to carry out inspection on transmission lines, substations and distribution lines. However, the traditional way has some problems such as fixed power lines and single inspection target. And because of the independence of power transmission, transformation and distribution departments, the total demand for UAV and UAV controllers is large, and it is difficult to realize the integration of equipment, personnel and technology. In order to further improve the level of lean management, maintenance efficiency of the whole system of transmission, transformation and distribution, and realize scheduling UAV inspection tasks autonomously, this paper establishes a mathematical model based on the genetic algorithm, taking the UAV inspection route planning as the core problem, and taking the shortest total route as the objective function, and iteratively calculates the collected data through the genetic algorithm to obtain the optimal solution, which is finally concluded by analysis and conclusion. By using this model algorithm to plan the route of multi-professional UAV inspection, the total route of UAV inspection has been dramatically reduced, human resources have been reasonably allocated, and the power line inspection has become comprehensive and efficient. Regarding the emergency response speed of UAV inspection, this study selects the nearest nest response to make the nests interact with each other. The hangars that intersect within the coverage can be intelligently coordinated through the task priority to achieve the fastest and most appropriate automatic execution of UAV tasks and effectively improve emergency response efficiency.
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