Comparison of genetic algorithm based evaluation of roundness with evaluation of roundness based on least squared method

LI Zi-fang; CUI Chang-cai; CHE Ren-sheng; HUANG Qing-cheng; YE Dong

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Comparison of genetic algorithm based evaluation of roundness with evaluation of roundness based on least squared method

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- Comparison of genetic algorithm based evaluation of roundness with evaluation of roundness based on least squared method
- Optics and Precision Engineering Vol. 11, Issue 3, Pages: 256-261(2003)
- 作者机构：
  
  1. 大庆石油学院电子工程系,黑龙江大庆,163400
  2. 哈尔滨工业大学305信箱,黑龙江哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：
  CLC： O436.1
- Received：15 December 2002，
  
  Revised：27 March 2003，
  
  Published Online：15 June 2003，
  
  Published：15 June 2003
- 稿件说明：
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李子芳, 崔长彩, 车仁生, 黄庆成, 叶东. 基于遗传算法的圆度公差评定法与采用最小二乘法评定的比较[J]. 光学精密工程, 2003,(3): 256-261

LI Zi-fang, CUI Chang-cai, CHE Ren-sheng, HUANG Qing-cheng, YE Dong . Comparison of genetic algorithm based evaluation of roundness with evaluation of roundness based on least squared method[J]. Editorial Office of Optics and Precision Engineering, 2003,(3): 256-261
李子芳, 崔长彩, 车仁生, 黄庆成, 叶东. 基于遗传算法的圆度公差评定法与采用最小二乘法评定的比较[J]. 光学精密工程, 2003,(3): 256-261 DOI：

LI Zi-fang, CUI Chang-cai, CHE Ren-sheng, HUANG Qing-cheng, YE Dong . Comparison of genetic algorithm based evaluation of roundness with evaluation of roundness based on least squared method[J]. Editorial Office of Optics and Precision Engineering, 2003,(3): 256-261 DOI：

摘要

根据提出的计算模型

对基于遗传算法的圆度误差评定和传统上采用最小二乘法的评定算法进行了比较分析

根据方法本身的特点和计算结果

分析了二者的不同点以及在工程应用中的适用场合.所构造的模型包括边界控制点和区域随机点

其中边界控制点模拟了由圆度误差最小区域条件所定义的最大内切圆和最小外切圆

而区域随机点模拟了实际情况下测试点的随机性和不确定性.计算结果表明基于遗传算法的圆度评定法精度较高

优于基于最小二乘法的评定算法.

Abstract

The evaluation of roundness based on genetic algorithm method(GAM) is compared with the evaluation of roundness based on least square method(LSM) with their advantages and drawbacks discussed in detail using the model proposed

which features bounds control data to simulated the maximum inscribed and maximum circumscribed circles defined under minimum zone conditions

and randonly produced data to simulate the randomness and uncertainties of test points under actual conditions. The computational results show that the accuracy of GAM is better than that of LSM.

关键词

Keywords

references

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CUI Chang-cai

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