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。
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.
作者
杨健
赵宏宇
YANG Jian ZHAO Hong-yu(College of Nuclear Technology and Automation Engineering, Chengdu University of Technology ,Chengdou 610059, China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2017年第3期706-711,共6页
Optics and Precision Engineering
基金
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(No.10912-JXTD201501)
关键词
遗传算法
退火算法
最小包容区域
平面度误差评定
genetic algorithm
annealing algorithm
minimum zone
flatness error evaluation
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
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.
