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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
According to the proposed calculation model, the roundness error evaluation based on genetic algorithm and the traditional least squares method are compared and analyzed. According to the characteristics of the method and the calculation results, the differences between the two methods are analyzed. In the application of the occasion. The constructed model includes the boundary control points and the region random points. The boundary control points simulate the maximum inscribed circle and the minimum circumscribed circle defined by the minimum area error of circularity error, while the random points in the region simulate the actual test points Randomness and uncertainty. The results show that the circularity evaluation method based on genetic algorithm is more accurate than the least square based evaluation algorithm