基于爬山遗传算法的三坐标测量路径优化

doi:10.3969/j.issn.1000-1158.2016.03.03

摘要
图/表
参考文献(16)
相关文章 (15)

全文: PDF (3691 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要针对传统遗传算法(GA)进行三坐标测量路径优化时收敛速度慢且过早收敛的问题,提出基于爬山遗传算法（HCGA）的三坐标测量路径优化方法。根据三坐标测量路径优化的数学模型,构造适合于测量路径优化问题的遗传编码、初始种群、选择、交叉、变异等参数,通过增加爬山操作,加快GA的迭代收敛速度。仿真实验结果表明,基于HCGA的三坐标测量路径优化方法能有效提高局部寻优能力与收敛速度,可获得很好的最优解并提高了测量效率。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	吴凤和
	孙迎兵
	王鑫

关键词 ：计量学, 三坐标测量机, 测量路径优化, 遗传算法, 爬山遗传算法

Abstract：Aiming at the problem of slow convergence speed and premature convergence in using the genetic algorithm to conduct the measuring path optimization in Coordinate Measuring Machine, the path optimization algorithm in Coordinate Measuring Machine based on Hill-climbing Genetic Algorithm was proposed. According to characteristics of the path optimization in Coordinate Measuring Machine, the mathematic model of the measuring path optimization was built and the parameters of coding, initial group, selection, cross for measuring path optimization problems were constructed. In addition, the climbing was added to increase convergence speed of the genetic algorithm for the global optimal solution. Besides, the simulation was programmed to verify the effectiveness of the Hill-climbing Genetic Algorithm and the application examples were used. Results show that when using the Hill-climbing Genetic Algorithm to conduct the path optimization algorithm in Coordinate Measuring Machine, the local optimization ability of genetic algorithm and the convergence speed were improved and the very good optimal solution was obtained. Therefore, the measuring efficiency was improved.

Key words： metrology CMM optimization of measuring path GA HCGA

收稿日期: 2015-07-13 发布日期: 2016-03-22

PACS:

TB92

基金资助:国家科技重大专项课题(2013ZX04003-031);高等学校博士学科点专项科研基金(20121333110011);河北省高等学校自然科学研究重点项目(ZD20131066)

通讯作者: 吴凤和 E-mail: risingwu@ysu.edu.cn

作者简介: 吴凤和(1968-),男,内蒙古扎兰屯人,燕山大学教授,博士生导师,主要研究方向为数字化测量与建模、智能制造与数字化制造。risingwu@ysu.edu.cn

引用本文:

吴凤和,孙迎兵,王鑫. 基于爬山遗传算法的三坐标测量路径优化[J]. 计量学报, 2016, 37(3): 235-240.
WU Feng-he,SUN Ying-bing,WANG Xin. Path Planning Method Based on HCGA in Coordinate Measuring Machine. Acta Metrologica Sinica, 2016, 37(3): 235-240.

链接本文:

http://jlxb.china-csm.org:81/Jwk_jlxb/CN/10.3969/j.issn.1000-1158.2016.03.03 或 http://jlxb.china-csm.org:81/Jwk_jlxb/CN/Y2016/V37/I3/235

［1］周菊香. 测量助推现代制造腾飞［J］. 航空精密制造技术, 2008, 44(3):27-29.
［2］ Lin Y J, Murugappan P. A new algorithm for determining a collision-free path for a CMM Probe ［J］.International Journal of Machine Tools & Manufacture, 1999, 39: 1397-1408.
［3］Lu C G, Morton D, Wu M H, et al. Genetic algorithm modelling and solution of inspection path planning on a coordinate measuring machine (CMM)［J］. The International Journal of Advanced Manufacturing Technology, 1999, 15: 409-416.
［4］王伯平, 王薇, 孙大刚, 等. 基于混沌遗传算法的圆度误差测量［J］. 计量学报, 2009, 30(6):514-516.
［5］王学影, 岩君芳, 叶树亮, 等. 关节臂式坐标测量系统关键技术研究［J］. 中国计量学院学报, 2010,21(1):12-15.
［6］Qu L.S, Xu G H, Wang G H. Optimization of the measuring path on a coordinate measuring machine using genetic algorithms［J］.Measurement,1998, 23（3）:159-170.
［7］王世刚. 基于CMM测量路径优化算法的研究［J］. 机械科学与技术, 2005, 24(5): 606-608.
［8］高国军, 陈康宁, 张申生. CMM测量中检测点数量和分布的规划方法［J］.上海交通大学学报,2007,33(9): 1164-1166.
［9］高延峰, 王孙安. 基于遗传算法的自由曲面测量路径规划［J］. 机床与液压, 2003, (6): 275-277.
［10］纪小刚, 龚光容. 三坐标测量机中基于遗传算法的多特征测量路径规划研究［J］. 兵工学报, 2005, 26(3):392-396.
［11］王萍, 谢驰, 廖世鹏. 三坐标测量机的空间曲面测量路径优化分析［J］. 中国测试技术, 2005, 31(2):30-32.
［12］文毅. 基于三坐标测量机的检测规划系统的研究与开发［D］. 西安:西安交通大学,2004.
［13］罗彪, 郑金华, 杨平. 基于定向爬山的遗传算法［J］. 计算机工程与应用, 2008, 44(6): 92-95.
［14］Melanie M. An introduction to genetic algorithms［M］. Boston: MIT Press, 1998:23-26.
［15］郎茂祥, 胡思继. 用混合遗传算法求解物流配送路径优化问题的研究［J］. 中国管理科学, 2002, 10(5): 51-56.
［16］Michalewicz Z, Fogel D B. How to solve it: modern heuristics［M］. Berlin: Springer-Verlag, 2000:14-19.