浮点数编码改进遗传算法在平面度误差评定中的研究

杨健; 赵宏宇

doi:10.3788/OPE.20172503.0706

您当前的位置：

首页 >

文章列表页 >

浮点数编码改进遗传算法在平面度误差评定中的研究

微纳技术与精密机械 | 更新时间：2020-07-07

- 浮点数编码改进遗传算法在平面度误差评定中的研究
- The research of floating-point codingimproved genetic algorithmin flatnesserror evaluation
- 光学精密工程 2017年25卷第3期页码：706-711
- 作者机构：
  
  成都理工大学核技术与自动化工程学院, 四川成都 610059
- 作者简介：
  
  杨健 (1972-), 女, 重庆人, 博士, 副教授, 硕士生导师, 成都理工大学核技术与自动化工程学院机电工程系主任, 主要从事先进制造技术领域的研究。E-mail:yangjian@cdut.edu.cn YANG Jian, E-mail:yangjian@cdut.edu.cn
  [ "赵宏宇 (1990-), 男, 吉林辽源人, 硕士研究生, 主要从事先进制造技术领域的研究。E-mail:471359350@qq.com" ]
- 基金信息：
  
  机器人，国家高技术863-809专题专家组;成都理工大学机械工程创新团队(10912-JXTD201501)
- DOI：10.3788/OPE.20172503.0706
  中图分类号：
- 收稿日期：2016-09-20，
  
  录用日期：2016-10-27，
  
  纸质出版日期：2017-03-25
- 稿件说明：
移动端阅览
杨健, 赵宏宇. 浮点数编码改进遗传算法在平面度误差评定中的研究[J]. 光学精密工程, 2017,25(3):706-711.

Jian YANG, Hong-yu ZHAO. The research of floating-point codingimproved genetic algorithmin flatnesserror evaluation[J]. Optics and precision engineering, 2017, 25(3): 706-711.
杨健, 赵宏宇. 浮点数编码改进遗传算法在平面度误差评定中的研究[J]. 光学精密工程, 2017,25(3):706-711. DOI： 10.3788/OPE.20172503.0706.

Jian YANG, Hong-yu ZHAO. The research of floating-point codingimproved genetic algorithmin flatnesserror evaluation[J]. Optics and precision engineering, 2017, 25(3): 706-711. DOI： 10.3788/OPE.20172503.0706.

摘要

随着智能制造系统的迅猛发展，应用元启发模式计算方法快速、准确地求解平面度误差值凸显出重大现实意义。为进一步提高平面度误差计算精度，研究了一种基于浮点数编码的改进遗传算法，在原有遗传算法的交叉变异基础之上，引入模拟退火思想，建立最小包容区域法的数学模型，通过计算机仿真获得了最佳适应度收敛曲线和平均适应度收敛曲线，优化结果表明相比传统遗传算法，平面度误差计算精度提高了33.67%。本算法采用浮点数编码、三段式交叉、转轮式选择和最优保存策略，借助模拟退火算法的局部搜索优势，提升了算法的整体性能，且更便于计算机编程，可进一步推广应用到智能测量仪器的其他高精度形位尺寸计算问题领域。

Abstract

With rapid development of intelligent manufacturing system

using Meta heuristic method to quickly and accurately calculate the flatness error is of great practical significance. To further improve the accuracy of flatness error calculation

an improved genetic algorithm based on floating-point coding was studied. In this method

the simulated annealing idea was introduced and a mathematic model for minimum zone method was established based on crossover and variation of the original genetic algorithm; and then the optimal fitness convergence curve and average fitness convergence curve were obtained through computer simulation. The optimization results show that compared with traditional genetic algorithm

the accuracy of flatness error calculation is improved by 33.67%. The algorithm adopts floating-point coding

three section cross

turning wheel selection and optimal preservation strategy; and its overall performance can be improved by local search advantage of the simulated annealing algorithm. Being more convenient for computer programming

the algorithm can be further applied to other high-accuracy position and dimension calculations of intelligent measuring instruments.

关键词

Keywords

references

SHARMA R, RAJAGOPAL K, ANAND S.A genetic algorithm based approach for robust evalution of form torlerances [J].Journal of Manufacturing Systems, 2000, 19(1):46-56.

TSENG H Y.A genetic algorithm for assessing flatness in automated manufacturing systems [J].Journal of Intelligent Manufacturing, 2006, 17(3):301-306.

崔长彩, 张耕培, 傅师伟, 等.利用粒子群优化算法的平面度误差评定[J].华侨大学学报 (自然科学版), 2008 29(4):507-509.

CUI C C, ZHANG G P, FU SH W, et al..Particle swarm optimization-based flatness evaluation [J]. Journal of Huaqiao University: Natural Science, 2008, 29(4):507-509.(in Chinese)

雷贤卿, 李飞, 涂鲜萍, 等. [J].光学精密工程, 2013, 21(5):1312-1317.

LEI Q X, LI F, TU X P, et al..Geometry searching approximation algorithm for flatness error evaluation [J]. Opt. Precision Eng., 2013, 21(5):1312-1317.(in Chinese)

罗钧, 王强, 付丽.改进蜂群算法在平面度误差评定中的应用[J].光学精密工程, 2012, 20(2):422-430.

LUO J, WANG Q, FU L. Application of modified artificial bee colony algorithm to flatness error evaluation [J].Opt. Precision Eng., 2012, 20(2):422-430.(in Chinese)

邓博于, 赵尚弘, 侯睿, 等.基于遗传蚁群融合算法的混合链路中继卫星资源调度研究[J].红外与激光工程, 2015, 44(7):2211-2217.

DENG B Y, ZHAO SH H, HOU R, et al..Research for resource scheduling of relay satellite system with hybrid links based on fusion algorithm of genetic and ant colony[J]. Infrared and Laser Engineering, 2015.44(7):2211-2217.(in Chinese)

劳达宝, 周维虎.基于遗传算法的柱面光栅测角技术研究[J].红外与激光工程, 2015.44(7):2182-2188.

LAO D B, WEI W H. Cylindrical grating angle measurement technology based on genetic algorithm [J]. Infrared and Laser Engineering, 2015.44(7):2182-2188. (in Chinese)

王小平, 曹立明, 等.遗传算法与软件实现[M].西安:西安交通大学出版社, 2002.

WANG X P, CAO L M, et al.. Genetic algorithm and software implementation [M].Xi'an:Xi'an Jiaotong University Press, 2002.(in Chinese)

HUANG S T, FAN K C, WU J H. A new minimum zone method for evaluating flatness errors [J]. Prec.Eng, 1993, 15(1):25-32.

崔长彩, 车仁生, 罗小川, 等.基于实数编码遗传算法的平面度评定[J].光学精密工程, 2002, 10(1):36-40.

CUI CH C, CHE R SH, LUO X CH, et al..Flatness evaluation based on real coded genetic algorithm [J].Opt. Precision Eng., 2002, 10(1):36-40.(in Chinese)

温秀兰, 宋爱国.基于实数编码的改进遗传算法及在平面度误差评定中的应用[J].计量学报, 2003, 24(2):88-91.

WEN X L, SONG A G. Improved genetic algorithm based on real coding and its application in flatness error evaluation [J]. Acta Metrologica Sinica, 2003, 24(2):88-91.(in Chinese)

田社评, 韦红雨, 王志武.用遗传算法准确评定平面度误差评价[J].计量技术, 2007(1):66-69.

TIAN SH P, WEI H Y, WANG ZH W.Using genetic algorithm to accurately assess flatness error evaluation [J].Acta Metrologica Sinica, 2007(1):66-69.(in Chinese)

浏览量

621

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

航拍多光谱田间秸秆覆盖量反演模型的建立与优化

CAD立体模型多源匹配的ICF靶位姿测量

模糊PID控制的恒星光谱模拟

基于Bekker理论改进遗传算法的野外路径优化方法研究

高速扫描激光共聚焦显微内窥镜图像校正