改进的蜂群算法评定空间直线度误差  

Straightness error evaluation using modified artificial bee colony algorithm

作　　者：辛帅[1] 李研[1] 

机构地区：[1]重庆大学光电技术及系统教育部重点实验室,重庆400030

出　　处：《电子设计工程》2011年第13期64-66,共3页Electronic Design Engineering

基　　金：国防科工委国防军工计量"十一五"计划重点资助项目(B20301118)

摘　　要：建立了直线度误差的最小区域评定模型,提出了一种改进的蜂群算法并将其应用到直线度误差评定中。阐述了基本蜂群算法的原理,给出了评定直线度的目标函数,利用混沌序列的全局遍历性,混沌初始化蜜源位置,以期提高蜂群算法的鲁棒性。比较改进蜂群算法与两种典型群智能算法的实例计算结果,证明该算法评定球度误差时不仅收敛速度快、评价精度高,而且鲁棒性高,适用于形位误差的优化评定。The evaluation model of the minimum zone straightness error is established,and an improved Artificial Bee Colony（ABC） algorithm is proposed to evaluate the straightness error.The principle and implementation techniques of ABC are introduced and then target function of evaluation straightness error is given.Based on the ergodicity of chaotic series,the location of the nectar source is initialized by chaos,expect to enhance the robustness.Compared with two typical colony algorithms,illustrations show that the convergence rate is faster,the convergence precision is better and robustness is stronger.It is suited for the evaluation of form and size errors.

关 键 词：蜂群算法 混沌序列 直线度 最小区域法 

分 类 号：TP161[自动化与计算机技术—控制理论与控制工程]