A genetic algorithm-based research on drone trajectory planning strategy of cooperative inspection of transmission lines, substations and distribution lines

Yongdong Dai, Maofei Wang, Weihao Fan
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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.
基于遗传算法的输电、变电、配电线路协同巡检无人机轨迹规划策略研究
目前,传统的无人机(UAV)电力线巡检项目主要是利用无人机对输电线路、变电站、配电线路进行巡检。但传统的检测方式存在着线路固定、检测目标单一等问题。而且由于输变配电部门的独立性,对无人机及无人机控制器的总需求量较大,难以实现设备、人员、技术的一体化。为了进一步提高整个输变配电系统的精益管理水平和维护效率,实现无人机巡检任务的自主调度,本文以无人机巡检路线规划为核心问题,以总路线最短为目标函数,建立了基于遗传算法的数学模型。并通过遗传算法对采集到的数据进行迭代计算,得到最优解,最后通过分析和结论得出。利用该模型算法规划多专业无人机巡检路线,大大减少了无人机巡检总路线,合理配置了人力资源,实现了电力线巡检的全面高效。针对无人机巡检的应急响应速度,本研究选择最近的巢响应,使巢间相互作用。可通过任务优先级对覆盖范围内相交的机库进行智能协调,实现无人机任务最快速、最合适的自动执行,有效提高应急响应效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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