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基于GA-SA算法的无人机巡检输电铁塔三维航迹优化
引用本文:刘书山,刘兰兰,肖乔莎,郭昊,徐溧,陈彬.基于GA-SA算法的无人机巡检输电铁塔三维航迹优化[J].科学技术与工程,2023,23(6):2438-2446.
作者姓名:刘书山  刘兰兰  肖乔莎  郭昊  徐溧  陈彬
作者单位:三峡大学电气与新能源学院;智能带电作业技术及装备机器人湖南省重点实验室
基金项目:智能带电作业技术及装备(机器人)湖南省重点实验室开放性课题资助(2021KZD1001)
摘    要:无人机巡检输电铁塔本体和金具、绝缘子等附属部件的航迹优化属于典型的旅行商问题。由于巡检对象的结构复杂、巡检部件多,采用单一的启发式算法会造成航迹重叠、容易陷入局部最优解等问题。为此,考虑无人机航迹三维空间结构的特点,引入全局搜索能力强的遗传算法(genetic algorithm, GA)与局部收敛速度快的模拟退火算法(simulated annealing, SA)相结合的无人机三维航迹混合GA-SA寻优算法。以无人机巡检500 kV超高压交流双回鼓型塔为例,根据三维有限元仿真得到的无人机电磁防护安全距离为2 m,结合巡检对象及常见缺陷出现的位置确定了61个高空安全悬停点,分别采用GA、SA和混合GA-SA算法对无人机遍历高空安全悬停点的航迹进行优化。结果表明:混合GA-SA算法的迭代收敛次数相比GA和SA分别减小了45.6%与55.2%,最优航迹距离分别缩短了8.1%与8.9%,验证了所提方法的有效性。

关 键 词:无人机巡检  航迹优化  电磁防护安全距离  有限元方法  混合算法
收稿时间:2022/6/8 0:00:00
修稿时间:2023/2/28 0:00:00

3D track optimization of UAV inspection of transmission tower based on hybrid genetic-simulated annealing algorithm
Liu Shushan,Liu Lanlan,Xiao Qiaosh,Guo Hao,Xu Li,Chen Bin.3D track optimization of UAV inspection of transmission tower based on hybrid genetic-simulated annealing algorithm[J].Science Technology and Engineering,2023,23(6):2438-2446.
Authors:Liu Shushan  Liu Lanlan  Xiao Qiaosh  Guo Hao  Xu Li  Chen Bin
Institution:College of Electrical Engineering & New Energy, China Three Gorges University
Abstract:The track optimization of UAV inspection of transmission tower and accessories such as fittings and insulators is a typical Traveling Salesman Problem. Due to the complex structure of patrol objects and many patrol components, using a single heuristic algorithm will cause problems such as track overlap and easy to fall into local optimal solution. Therefore, considering the characteristics of three-dimensional spatial structure of UAV track, a hybrid GA-SA optimization algorithm of UAV three-dimensional track is introduced, which combines Genetic Algorithm (GA) with strong global search ability and Simulated Annealing (SA) with fast local convergence speed. Taking the UAV inspection of 500 kV EHV AC double circuit drum tower as an example, according to the three-dimensional finite element simulation, the electromagnetic protection safety distance of UAV is 2 m. Combined with the patrol object and the location of common defects, 61 high-altitude safety hovering points are determined. GA, SA and hybrid GA-SA algorithms are used to optimize the track of UAV traversing high-altitude safe hovering points. The results show that compared with GA and SA, the iterative convergence times of hybrid GA-SA are reduced by 45.6% and 55.2% respectively, and the optimal track distance is shortened by 8.1% and 8.9% respectively, which verifies the effectiveness of the proposed method.
Keywords:UAV inspection  track optimization  electromagnetic protection safety distance  finite element method  hybrid algorithm
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