【作者】 陈伟；

【导师】 赵德安；

【作者基本信息】 江苏大学 ， 控制理论与控制工程， 2013， 博士

【摘要】 喷涂机器人是一种重要的先进涂装生产装备,在国内外广泛应用于汽车等产品的涂装生产线。喷涂机器人的喷涂效果与物体表面形状、喷涂过程参数等诸多因素有关。为了达到新的喷涂作业标准,实现高效低成本的生产目标,对新喷涂建模的分析以及高性能喷涂机器人轨迹优化算法、控制策略的研究已成为国内外学者们关注的热点。本课题以国家自然科学基金项目和江苏省高技术研究项目为背景,对喷涂机器人轨迹优化技术中的一些难点问题和关键问题进行研究,研究内容主要由以下几个部分构成：第一,针对工业生产中喷涂工件复杂多样的特点,提出了两种适用于不同场合且实用性较强的喷涂工件曲面造型方法：一种是基于平面片连接图FPAG的曲面造型方法,该方法先对曲面进行三角网格划分,再将划分后的三角面连接成平面片,最后使用基于平面片连接图FPAG的合并算法将各个平面片连接成为较大的片；另一种是基于点云切片技术的曲面造型方法,该方法主要分为总体算法描述、切片层数的确定、切片数据的分离、切片数据计算、多义线重构等五个部分。实验结果表明,这两种方法分别可以应用于一般性曲面以及曲率变化大的工件曲面的造型,并且计算速度快,完全满足喷涂机器人工作的需要,从而为后续的喷涂机器人轨迹优化工作奠定了基础。第二,提出了从规划喷涂路径角度优化喷涂轨迹、提高喷涂质量的思想。根据喷涂机器人实际工作的需要,提出两种喷涂机器人空间路径规划方法：一种是基于分片技术的喷涂机器人空间路径规划,该方法主要是应用于复杂曲面上的路径规划,将复杂曲面分片问题表示为一个带约束条件的单目标优化问题,并给出相应的分片算法,再建立每一片喷涂路径的评价函数,并以此为依据来规划喷涂路径,从而为获得更佳的优化轨迹并得到更好的喷涂效果提供了基础；另一种是基于点云切片技术的喷涂机器人空间路径规划,该方法通过设定切片方向和切片层数,对点云模型进行切片处理,得到切片多义线后对其平均采样,然后估算所有采样点的法向量,最后利用偏置算法获取喷涂机器人空间路径。实验结果表明,这两种方法都比较实用,且计算速度较快,能够在保证喷涂机器人喷涂效率的同时,达到更佳的喷涂效果。第三,针对实际工业生产中许多喷涂工件形状复杂,喷涂时会遇到多个喷涂面且各个喷涂面的法向量夹角都比较大的问题,提出了面向三维实体的喷涂机器人空间轨迹优化方法。利用实验方法建立一种简单的涂层累积速率数学模型并采用基于平面片连接图FPAG的曲面造型方法对三维实体进行分片；规划出每一片上的喷涂路径后,以离散点的涂层厚度与理想涂层厚度的方差为目标函数,在每一片上进行喷涂轨迹的优化,并按照两片交界处空间路径方向的不同分PA-PA、PA-PE、PE-PE三种情况研究了两片交界处的喷涂轨迹优化情况,仿真实验结果表明两片交界处的喷涂空间路径为PA-PA时涂层厚度均匀性最佳；采用哈密尔顿图形法表示各个分片上的喷涂轨迹优化组合问题,分别采用GA算法、ACO算法、PSO算法对其进行求解,并通过仿真实验验证了各个算法的可行性。最后,在自行设计的喷涂机器人离线编程实验平台上进行了喷涂实验,并对几种算法结果进行了比较。实验结果表明,提出的面向三维实体的喷涂机器人轨迹优化方法完全能满足涂层厚度均匀性的要求；而使用PSO算法虽然需要消耗少量的系统运算执行时间,但与其他算法相比更加节约喷涂时间,显著提高了喷涂效率。第四,针对范围在十几米内,各局部法向量方向差异不大的自由曲面或复杂曲面上的喷涂问题,提出了曲面上的喷涂机器人空间轨迹优化方法。首先研究了自由曲面上的喷涂轨迹优化方法：采用实验方法建立了表达式较简单的涂层累积速率模型后,通过分析喷涂过程中各个可控参数对喷涂效果的影响,建立自由曲面上涂层厚度数学模型；在此基础上生成喷涂机器人空间路径,得出轨迹优化设计是带约束条件的多目标优化问题,并选取时间最小和涂层厚度方差最小作为目标函数,应用带权无穷范数理想点法进行求解；仿真实验和喷涂实验表明,该算法完全符合预设的喷涂质量和喷涂效率的要求。其次,研究了曲面上的静电喷涂机器人轨迹优化问题,在利用实验方法得到静态喷涂涂料空间分布的径向厚度剖面函数后,推导出一种新型、实用的ESRB涂层累积模型：以某品牌汽车车身为喷涂对象进行静电喷涂实验研究,并对喷涂结果进行了分析和讨论。更多还原

【Abstract】 Painting robot is a kind of important and advanced spray equipment. It is widely used in automotive manufacturing. The figure of a product and the tool parameters can strongly influence the quality of painting. In order to achieve the new spraying operation standards,new painting models and tool planning algorithms are active research for many years. This work is supported in part by the national natural science foundation program and in part by the high-tech research program of Jiangsu. The main work of this dissertation consists of four parts as follows:Firstly, due to the complex geometry of free-form surfaces, it is still a challenge to generate optimization trajectories of spray gun that satisfies paint uniformity requirements.And two methods of surface modeling are introduced. The triangular representation of a surface is introduced first. This paper discuss the construction of the flat patch adjacency graph (FPAG). Based on the FPAQ a merging algorithm is proposed to form big patches. Then another method of point cloud is discussed.The relative algorithms of point cloud slicing are deeply researched,including the determination of slicing thickness,the choice of slicing direction,the calculation of slicing date,the reconstruction of poly-lines etc.,so that the uniform slicing of point cloud is completed. The experimental results illustrate the feasibility andavailability of these algorithms.Secondly, two methods of tool path planning in spray forming processes are introduced. This paper proposes a tool path planning approach which optimizes the tool motion performance and the thickness uniformity. There are two steps in this approach. The first step partitions the part surface into flat patches based on the topology and normal directions.The second step determines the tool movement patterns and the sweeping directions for each flat patch. Based on the above twosteps, optimal tool paths can be calculated. Then another tool path planning method of point cloud is discussed. The point cloud data is obtained by scanning the surface of work piece, then slicing the point cloud data to estimate the normal vectors of the sampled points, so the tool path is formed through offsetting the distance between spray gun and work piece along the normal vectors. Experimental tests are carried out and the results validate the proposed approach.Thirdly, trajectory optimization of painting robot for3D solid is studied. A3D solid is divided into several patches by the evaluation function and trajectory optimization for each patch is performed. In order to satisfy the material uniformity requirements, optimization algorithms of the three different cases are developed to integrate the trajectories on the intersecting area of two patches. Tool trajectory for geometry-complicated parts are generated by partitioning them into individual surfaces,generating the trajectories for each partition, and then, interconnecting the trajectories from the different patches so as to minimize the overall path length. Three different solutions are presented to tool trajectory optimal integration problem.The first solution is based on genetic algorithms.The second one is based on ant colony optimization and the third one is based on particle swarm optimization. Experimental results demonstrate the effectiveness of the three methods and the quality of solutions that can be achieved.Finally, trajectory optimization of painting robot for surfaces is studied. Trajectory optimization of free-form surfaces is introduced firstly. Because the current paint deposition rate function is too complicated, the paint deposition rate function on a plane according to the experiment data is provided. The paint thickness function for free-form surfaces is also given. A multi-objective constraint optimization problem is formulated. An optimal tool trajectory with an optimal time and film quantity deviation is generated. And ideal point method is adopted here to calculate the values by iteration. Then the paint deposition rate function of electrostatic rotary bell applicator according to the experiment data is provided. The electrostatic spray painting experiment on automobile demonstrates the feasibility and availability of these optimization algorithms.更多还原