多目标夹具布局建模与基于Memetic算法的优化设计
发布时间：2019-06-18 21:02
【摘要】：机床夹具是在生产制造过程中被广泛应用的夹持装备,用于工件在机床工作台上的定位和夹紧。夹具定位元件的制造和安装误差以及工件定位稳定性等因素会导致工件产生位姿偏差,即工件的实际位置与理论位置存在误差,最终导致工件产生加工误差。通过分析夹具定位布局对工件定位精度与稳定度的影响,建立了多目标夹具布局模型,可以准确获得由已知定位误差所导致的工件位姿偏差,进而对夹具进行优化设计以减小工件的位姿偏差。本文主要对夹具布局进行研究,完成了以下工作:首先,分析了机床夹具的定位误差与工件位姿偏差之间的关系,建立了描述工件位姿误差与夹具各定位元件误差之间的定位精度模型,求得由已知的夹具定位误差引起的工件位姿误差;分析了工件的定位稳定性与定位点布局的整体几何图形之间的关系,建立了工件定位稳定性模型。通过调整每个定位点的位置来调整夹具定位布局的的几何分布,最终使得工件的定位最稳定,从而在加工过程中减少工件的偏转或位移,进而使得工件的位姿偏差最小,提高工件的加工精度。其次,由于工件的位姿误差模型与定位布局的几何稳定性模型都与夹具定位点位置相关。因此,将工件的位姿误差模型与定位布局的几何稳定性模型联立,组成最小化的多目标夹具布局优化模型。该模型综合考虑了影响工件位姿偏移的稳定性因素与定位点的误差因素,在给定各个定位点的误差时,通过对目标函数的优化,使得工件位姿偏移量最小、工件定位更稳定,最终提高工件的加工精度。最后,提出了一种基于Memetic Algorithms(MA)的多目标夹具布局优化的新方法。通过熵权法计算得出每个目标函数的权系数,再将各目标函数的权系数乘以其对应的目标函数,相加求和得到评价函数。之后再利用MA优化计算出评价函数的最优值,也就获得了最优夹具布局。通过与基于GA(遗传算法)的单目标优化方法得出工件位姿偏移最小量的结果进行对比验证多目标夹具布局优化模型的正确性;MA与GA的收敛性对比,验证文中所提出的多目标优化方案的有效性和可行性。
[Abstract]:The machine tool fixture is a kind of clamping equipment which is widely used in the production and manufacturing process, and is used for the positioning and clamping of the work piece on the working platform of the machine tool. The manufacturing and installation errors of the fixture positioning elements and the positioning stability of the work pieces can cause the workpiece to generate the pose deviation, that is, the actual position of the workpiece and the theoretical position are errors, and finally the work piece is caused to generate machining errors. By analyzing the influence of the fixture positioning layout on the positioning accuracy and stability of the workpiece, a multi-objective fixture layout model is established, and the position and pose deviation of the workpiece caused by the known positioning error can be accurately obtained, and then the clamp can be optimized and designed to reduce the pose deviation of the workpiece. In this paper, the fixture layout is studied, the following work is completed: firstly, the relation between the positioning error of the machine tool fixture and the position and position deviation of the workpiece is analyzed, the positioning accuracy model between the position and the position error of the workpiece and the error of each positioning element of the clamp is established, The position and pose error of the workpiece caused by the known fixture positioning error is obtained, the relation between the positioning stability of the workpiece and the whole geometric figure of the positioning point layout is analyzed, and the positioning stability model of the workpiece is established. And the position of each positioning point is adjusted to adjust the geometric distribution of the fixture positioning layout, and finally, the positioning of the workpiece is most stable, so that the deflection or displacement of the workpiece is reduced during the machining process, so that the pose deviation of the workpiece is minimized, and the machining accuracy of the workpiece is improved. Secondly, because the position and pose error model of the workpiece and the geometric stability model of the positioning layout are all related to the position of the positioning point of the fixture. Therefore, the pose error model of the workpiece and the geometric stability model of the positioning layout are combined to form a minimized multi-objective fixture layout optimization model. According to the model, the error factors of the stability factors and the positioning points of the workpiece pose deviation are comprehensively considered, and when the error of each positioning point is given, the position and position deviation of the workpiece is minimized by the optimization of the objective function, and the positioning of the workpiece is more stable, and the processing precision of the workpiece is finally improved. In the end, a new method of multi-target fixture layout optimization based on Metic Algorithm (MA) is presented. The weight coefficient of each objective function is calculated by the entropy method, then the weight coefficient of each objective function is multiplied by the corresponding objective function, and the sum is added and summed to obtain the evaluation function. Then, the optimal value of the evaluation function is calculated by MA optimization, and the optimal fixture layout is obtained. The validity and feasibility of the multi-objective optimization scheme proposed in this paper are verified by comparing the results of the method of single target optimization based on GA (Genetic Algorithm) to verify the correctness of the multi-objective fixture layout optimization model.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TG75
本文编号：2501795
[Abstract]:The machine tool fixture is a kind of clamping equipment which is widely used in the production and manufacturing process, and is used for the positioning and clamping of the work piece on the working platform of the machine tool. The manufacturing and installation errors of the fixture positioning elements and the positioning stability of the work pieces can cause the workpiece to generate the pose deviation, that is, the actual position of the workpiece and the theoretical position are errors, and finally the work piece is caused to generate machining errors. By analyzing the influence of the fixture positioning layout on the positioning accuracy and stability of the workpiece, a multi-objective fixture layout model is established, and the position and pose deviation of the workpiece caused by the known positioning error can be accurately obtained, and then the clamp can be optimized and designed to reduce the pose deviation of the workpiece. In this paper, the fixture layout is studied, the following work is completed: firstly, the relation between the positioning error of the machine tool fixture and the position and position deviation of the workpiece is analyzed, the positioning accuracy model between the position and the position error of the workpiece and the error of each positioning element of the clamp is established, The position and pose error of the workpiece caused by the known fixture positioning error is obtained, the relation between the positioning stability of the workpiece and the whole geometric figure of the positioning point layout is analyzed, and the positioning stability model of the workpiece is established. And the position of each positioning point is adjusted to adjust the geometric distribution of the fixture positioning layout, and finally, the positioning of the workpiece is most stable, so that the deflection or displacement of the workpiece is reduced during the machining process, so that the pose deviation of the workpiece is minimized, and the machining accuracy of the workpiece is improved. Secondly, because the position and pose error model of the workpiece and the geometric stability model of the positioning layout are all related to the position of the positioning point of the fixture. Therefore, the pose error model of the workpiece and the geometric stability model of the positioning layout are combined to form a minimized multi-objective fixture layout optimization model. According to the model, the error factors of the stability factors and the positioning points of the workpiece pose deviation are comprehensively considered, and when the error of each positioning point is given, the position and position deviation of the workpiece is minimized by the optimization of the objective function, and the positioning of the workpiece is more stable, and the processing precision of the workpiece is finally improved. In the end, a new method of multi-target fixture layout optimization based on Metic Algorithm (MA) is presented. The weight coefficient of each objective function is calculated by the entropy method, then the weight coefficient of each objective function is multiplied by the corresponding objective function, and the sum is added and summed to obtain the evaluation function. Then, the optimal value of the evaluation function is calculated by MA optimization, and the optimal fixture layout is obtained. The validity and feasibility of the multi-objective optimization scheme proposed in this paper are verified by comparing the results of the method of single target optimization based on GA (Genetic Algorithm) to verify the correctness of the multi-objective fixture layout optimization model.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TG75
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