【作者】 李博；

【导师】 单光坤； 陈世刚； 马铁强；

【作者基本信息】 沈阳工业大学 ， 机械硕士（专业学位）， 2023， 硕士

【摘要】 风机叶片作为风力发电机的主要组成部分,其制造成本约占风机总成本1/4。安装环境、自然灾害、疲劳损伤等问题以及人工操作不当等都容易造成风机叶片故障,会给风电场造成巨大经济损失并且存在安全隐患。因此,风力机叶片日常损伤检测十分重要,研究人员正在开展巡检机器人相关研究,用巡检机器人代替人工检测。本文提出了一种新型的基于风机叶片静强度仿真分析建图的巡检机器人路径规划方法,主要研究此类巡检机器人的路径规划及运动控制方法,仅以强度分析应力云图为例,来构建地图,在实际应用中应加入疲劳等多种情况。论文主要研究内容如下:首先,以美国桑迪亚国家实验室公开发布的5MW风机叶片为研究对象,通过叶素动量理论分析,推导出风力机叶片的空气动力载荷计算公式,计算出风机叶片空气动力载荷,用坐标导入法建立风力机叶片的三维模型,利用有限元分析软件进行网格划分、材料铺层、载荷施加等处理,仿真分析得出巡检机器人路线规划环境建模所需的风力机叶片静强度应力云图。其次,对应力云图进行栅格化处理,得到巡检机器人的全局巡检路径规划环境地图。在传统A*算法的基础上,引入权重系数对算法进行改进,并对规划结果进行拐角优化,最后通过三次样条插值曲线对规划路线进行了平滑处理,以减少路径长度、提高搜索效率。使用仿真软件设定六种不同的权重值进行实验并对比分析选出最优权重值,针对最优结果分别进行了拐角优化和路径平滑仿真实验,以验证优化算法。最后,在ROS平台建立叶片巡检机器人模型,导入Gazebo中。将风力机叶片模型设置为封闭空间,通过墙体以及内部添加固定障碍物的形式构建仿真环境模型,论文中障碍物识别主要以激光雷达为主,路径规划为论文主要内容,基于Gazebo与Rviz通过改进后的A*算法对叶片巡检机器人进行运动控制联合仿真。仿真结果表明:本文提出的改进A*算法可以在无碰撞的情况下得到优化的巡检规划路线,能够完成既定的风力机叶片巡检任务。更多还原

【Abstract】 As the main component of wind turbines,the manufacturing cost of wind turbine blades accounts for about 1/4 of the total cost of wind turbines.Installation environment,natural disasters,fatigue damage and improper manual operation are easy to cause wind turbine blade failure,which will cause huge economic losses to wind farms and have potential safety hazards.Therefore,the daily damage detection of wind turbine blades is very important,and researchers are carrying out research on inspection robots,replacing manual inspection with inspection robots.This thesis mainly studies the path planning and motion control methods of such inspection robots,and proposes a path planning method for inspection robots based on static strength simulation analysis of wind turbine blades.Firstly,taking the 5MW wind turbine blade publicly released by Sandia National Laboratory as the research object,the aerodynamic load of the wind turbine blade is derived through the theoretical analysis of leaf momentum,the three-dimensional model of the wind turbine blade is established by the coordinate import method,and the finite element analysis software is used to mesh the meshing,material laying,load application and other processing,and the static strength stress cloud of the wind turbine blade required for the route planning environment modeling of the inspection robot is obtained by simulation analysis.Secondly,the stress cloud map is rasterized to obtain the global inspection path planning environment map of the inspection robot.On the basis of the traditional A* algorithm,the weight coefficient is introduced to improve the algorithm,the corner optimization of the planning results is carried out,and finally the planned route is smoothed by the cubic spline interpolation curve to reduce the path length and improve the search efficiency.Six different weight values were set by simulation software for experiments,and the optimal weight values were selected through comparative analysis,and two experiments,corner optimization and path smoothing,were carried out for the optimal results,so as to verify the optimization algorithm.Finally,a blade inspection robot model is established on the ROS platform and imported into Gazebo.The wind turbine blade model is set as a closed space,and the simulation environment model is constructed in the form of adding fixed obstacles to the wall and inside,and the motion control of the blade inspection robot is jointly simulated based on the improved A* algorithm by Gazebo and Rviz.The simulation results show that the improved A* algorithm in this thesis can obtain an optimized inspection planning route without collision,and can complete the established wind turbine blade inspection task.更多还原