基于GA-SA算法的无人机巡检输电铁塔三维航迹优化

3D Track Optimization of UAV(Unmanned Aerial Vehicles)Inspection of Transmission Tower Based on GA-SA

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。

The track optimization of UAV(unmanned aerial vehicles)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 was 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(extra-high voltage)AC(alternating current)double circuit drum tower as an example,according to the three-dimensional finite element simulation,the electromagnetic protection safety distance of UAV was 2 m.Combined with the patrol object and the location of common defects,61 high-altitude safety hovering points were determined.GA,SA and hybrid GA-SA algorithms were 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.