基于遗传算法的打磨机器人去除量工艺参数优化  

Optimization of Process Parameters of Polishing Robot Removal Volume Based on Genetic Algorithm

作　　者：苏成志 李星佐 姜丰 赵广 梅宇飞 SU Chengzhi;LI Xingzuo;JIANG Feng;ZHAO Guang;MEI Yufei(School of Artificial Intelligence,Changchun University of Science and Technology,Changchun 130022,China;School of Mechanical Engineering,Changchun University of Science and Technology,Changchun 130022,China;School of Telecommunications,Changchun University of Science and Technology,Changchun 130022,China)

机构地区：[1]长春理工大学人工智能学院,吉林130022 [2]长春理工大学机电工程学院,吉林130022 [3]长春理工大学电子信息工程学院,吉林130022

出　　处：《组合机床与自动化加工技术》2025年第2期184-187,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国防基础科研计划资助项目(JCKY2019411B001)。

摘　　要：针对材料表面余量精准去除问题,提出了一种基于遗传算法的打磨机器人去除量工艺参数优化方法。首先,以Preston方程和赫兹弹性接触理论为理论基础,建立去除量与工艺参数模型;其次,基于遗传算法以最小去除量误差值作为算法的优化目标对打磨工艺参数求最优解;最后,搭建打磨机器人系统进行优化前后的打磨对比实验验证。结果表明,在去除量值10μm~60μm范围内,该方法相较同类方法的材料去除量平均相对误差ε_(r)了降低13%左右,验证了该优化方法对材料表面余量去除的有效性。Aiming at the problem of accurate material surface margin removal,a genetic algorithm-based method for optimizing the process parameters of the removal amount of a polishing robot was proposed.First,based on the Preston equation and Hertzian elastic contact theory,a model of removal volume and process parameters is established;secondly,a genetic algorithm is used to find the optimal solution for the polishing process parameters with the minimum removal volume error value as the optimization goal of the algorithm;and finally,a polishing robot system is built.Conduct polishing comparison experiments before and after optimization to verify.The results show that the removal amount ranges from 10 μm~60 μm,Compared with similar methods,the average relative error ε_(r) of material removal is reduced by about 13%,The effectiveness of this optimization method in removing material surface margins is verified.

关 键 词：机器人打磨 打磨去除量 预测模型 优化模型 

分 类 号：TH16[机械工程—机械制造及自动化] TG58[金属学及工艺—金属切削加工及机床]