利用旅行推销员问题优化电力线检查

T. Moyo, Francois du Plessis
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引用次数: 3

摘要

经常检查电线和相关部件,以确保电力的质量供应。目前的电力线检查方法,如有人驾驶直升机和地面监视人员是昂贵的,使用无人驾驶飞行器(uav)已被提出作为一种经济有效的替代方案。本文介绍了一种方法的发展研究,以优化检查电力线和相关组件使用旋转无人机。提出了一种基于旅行商问题(TSP)的检测路径优化方法。在将此问题定义为TSP时,选择路径点是基于它们相对于需要检查的塔组件的位置。然后将这些航路点用作使用遗传算法求解的经典TSP中的城市。城市在MATLAB模型中使用,该模型具有缩放塔。仿真结果表明,将遗传算法和TSP算法结合使用有可能实现最优检测
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of the Travelling Salesman Problem To optimise power line inspections
Frequent inspections of power lines and the associated components is required to ensure quality supply of electricity. Current power line inspection methods such as manned helicopters and ground surveillance crews are expensive and the use of Unmanned Aerial Vehicles (UAVs) has been presented as a cost effective alternative. This paper presents research into the development of a method to optimise the inspection of power lines and associated components using a rotary UAV. The proposed inspection path optimisation is based on the Travelling Salesman Problem (TSP). In defining this problem as a TSP, waypoints are chosen based on their position relative to pylon components that require inspections. These waypoints are then used as cities in the classic TSP which is solved using a Genetic Algorithm. The cities are used in a MATLAB model that has a scaled pylon. The results obtained in simulation show that there is a potential for using the proposed combination of GA and TSP to enable optimal inspections
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