摘要
针对传统最小二乘圆优化算法评定圆度误差局部收敛的问题,提出基于遗传算法的圆度误差评定方法。介绍了遗传算法基本原理和运算流程,在建立最小二乘圆数学模型的基础上,推导出待优化的目标函数,并详细描述了基于遗传算法的圆度评定优化步骤。实例计算结果表明该算法能比传统优化算法收敛到更精确的解,并具有较高的稳定性,能有效地克服局部收敛的问题。
In order to overcome the local convergence problem when optimizing the least square circle with traditional algorithms, a method of evaluating roundness error based on genetic algorithm （GA） is proposed. The basic principle and operation process of GA are introduced. Based on the mathematical model of least square circle, the objective function to be optimized is derived, and the calculating steps of roundness evaluation based on GA are presented in detail. The calculation result of example shows that GA obtains a more accurate result compared to the traditional algorithms, and has a high stability. The algorithm can overcome the local convergence problem effectively.
出处
《测控技术》
CSCD
北大核心
2014年第8期33-36,共4页
Measurement & Control Technology
关键词
圆度误差
最小二乘圆
遗传算法
局部收敛
roundness error
least square circle
genetic algorithm
local convergence
