摘要
为实现最小区域平面度误差准确评定,提出了一种基于种群优化的微分进化算法。同其他平面度误差评定方法相比,该算法具有简单灵活、效率高、搜索能力强、鲁棒性好、控制参数少等特点。该优化算法包含种群初始化、变异、交叉、选择等步骤,能快速实现对目标函数的全局优化搜索。依照ISO标准,从平面度最小区域解决方案定义出发,给出了微分进化算法实现平面度误差目标函数数学模型建立方法。最后通过多个实验及与不同评价方法对同一平面的平面度误差评定结果进行比较,验证了微分进化算法用于平面度误差评定的快速收敛性、高稳定性和有效性,适宜于对高精度平板准确快速评定。
A differential evolutionary algorithm （DE） based on population optimization is proposed to implement precise evaluation of the minimum zone flatness errors.Compared with other methods,it is simplicity,good flexibility,efficient,robust and less control parameters.This optimization algorithm contains population initialization,mutation,crossover,and selection and can quickly realize the global optimization search for objective function.Then,the objective function calculation model of planar error are developed,which directly originate from the definition of minimum zone solution and conform to the ISO standard.Finally,the rapid convergence,high stability and effectiveness of the proposed DE algorithm are confirmed though the experimental evaluated results by comparing with different evaluation methods.It is suitable for the high precision flat fast evaluation.
出处
《组合机床与自动化加工技术》
北大核心
2013年第12期18-20,24,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金(51075198)
江苏省自然科学基金(BK2010479)
南京工程学院创新基金(CKJ2011004)
关键词
智能计算
微分进化
平面度误差
最小区域法
intelligent computation
differential evolutionary
flatness error
minimum zone solution
