风机自主巡视的无人机控制策略研究

Research on control strategy of UAV for autonomous inspection of wind turbine

应用旋翼无人机对风力发电机进行自主巡视时,需正对风机采集全景图,计算桨叶空间位置,进而对巡视航线和航点做出规划。为此提出一种风机自主巡视的无人机控制策略。首先,采用Yolov5神经网络模型对风机各部位进行提取,同时利用风机各部位像素坐标计算无人机位姿修正量并设计控制器,使无人机到达正对风机的位置对其全景图进行采集;其次,根据全景图计算桨叶叶尖的空间坐标,规划出巡视航线及初始航点,达到对桨叶的全面图像采集;最后,为克服定位误差等因素的干扰,设计控制器使无人机可依据图像信息进行位姿调整,使桨叶保持在图像中心位置,达到对风机精准巡视的目的。仿真试验表明,所提出的策略可达到对风力发电机自主巡视的目的,其中的设计思路也可为其他电力设备的巡检方案提供参考。

When the rotor UAV is used to inspect the wind turbine independently,it is necessary to collect the panorama of the wind turbine,calculate the spatial position of the blades,and then plan the inspection route and inspection point.Therefore,a UAV control strategy for autonomous inspection of wind turbines is proposed in this paper.Firstly,the Yolov5 neural network model is used to extract each part of the wind turbine.At the same time,the position and attitude correction of the UAV is calculated by using the pixel coordinates of each part of the wind turbine,and the controller is designed to make the UAV reach the position of directly facing the wind turbine to collect its panorama.Secondly,the spatial coordinates of the blade tips are calculated according to the panorama,and the patrol route and initial inspection points are planned to achieve a comprehensive image acquisition of the blades.Finally,in order to overcome the interference of positioning errors and other factors,a controller is designed so that the UAV can adjust the position and attitude according to the image information,so that the blade can be kept in the center of the image,so as to achieve the purpose of precision patrol of the wind turbine.The simulation results show that the strategy proposed in this paper can achieve the purpose of independent inspection of wind turbines,and the design ideas can also provide reference for the inspection schemes of other power equipments.