基于模糊神经网络的电力巡线无人机避障技术研究

随着国民经济持续稳定快速发展,,输电线路的巡检工作量日益加大,传统人工巡检已经不能满足当前输电线路巡检的需求。无人机电力巡线能够较好弥补人工巡检的不足,提高电力巡检作业的工作效率。为了获得精确的无人机与输电线路、杆塔以及附近障碍物的距离信息,采用了多传感器融合技术,通过对巡检过程中可能出现的障碍物进行建模,建立最小安全空间模型和输电线路周围电场模型,提出基于模糊神经网络的方法,对无人机电力巡线的避障技术进行了研究。仿真结果表明,该方法可以有效实现无人机在电力巡线中对障碍物的躲避。

Research on Obstacle Avoidance Technology of Unmanned Aerial Vehicle in Power Line Inspection

With the sustained, the scale of power grids in our country is expanding day by day, and the inspection workload of transmission lines is also increasing,traditional manual inspection has been unable to meet the requirements of the current transmission line inspection.UAV power line can make up for the lack of manual inspection,improve the work efficiency of power inspection. In order to obtain accurate UAV and transmission line tower and near the obstacle distance information,multi sensor fusion technology is adopted,by modeling the possible obstacles in the process of in-spection,to establish the minimum safe space model and the electric field distribution model of power line. Propose the method of obstacle avoidance based on fuzzy neural network and study the obstacle avoidance technology. The simula-tion results show that the method can effectively avoid the obstacle in the power line.