【摘要】 为提升圆柱度误差的计算精度，使评价结果更加理想，提出在圆柱度误差评价中应用GA遗传算法。实验中使用3组原始采样点数据，以最小区域法为例，由目标函数的寻优变量组成遗传算法的染色体，将最小区域法的目标函数作为遗传算法中的适应度函数，采用实数编码的方式，对获取的3组原始采样点数据进行寻优求解。实验结果表明，相比于3组数据的原求解结果，加入遗传算法后，数据1的精度提高了1.796%,数据2的精度提高了7.691%,数据3的精度提高了34.487%,证明GA遗传算法在圆柱度评价中能够提升圆柱度误差的计算精度，并且能够更精确地在空间中搜索到最优参数。更多还原

【Abstract】 In order to improve the calculation accuracy of cylindricity error and obtain more ideal evaluation results, the genetic algorithm was proposed for cylindricity error evaluation.In the experiment, three sets of original sampling point were used. Taking the minimum zone as an example, the chromosome of the genetic algorithm was composed of the optimization variables of the objective function and the objective function of the minimum region method was used as the fitness function in the genetic algorithm. The real number coding method was used to optimize the three sets of original sampling point.the experimental results showed that compared with the original solution results of the three sets of data and after adding the genetic algorithm, the accuracy of data 1 was increased by 1.796%, the accuracy of data 2 was increased by 7.691% and the accuracy of data 3 was increased by 34.487%.It is proved that genetic algorithm is able to improve the calculation accuracy of cylindricity error in cylindricity evaluation and to search the optimal parameters in space more accurately.更多还原