基于遗传算法的3-DOF并联机床机构的结构参数优化  

Structural Parameter Optimization of a 3-DOF Parallel Mechanism Based on Genetic Algorithm

作　　者：张虎[1] 郭志飞[2] 张铮[1] 徐安林[1] 

机构地区：[1]无锡职业技术学院机械技术学院,江苏无锡214121 [2]江苏大学机械工程学院,江苏镇江212013

出　　处：《机床与液压》2015年第3期20-23,33,共5页Machine Tool & Hydraulics

基　　金：国家科技部科技型中小企业技术创新基金项目(09C26213203835);无锡职业技术学院校级科研课题(KJ201314)

摘　　要：建立了3-P-(2U-2S)并联机床机构的反解方程,求解得到机床的工作空间。通过雅克比矩阵条件数的计算,得到并联机床机构的运动特性条件指标。以工作空间与全局条件指标(GCI)作为评价指标,应用BP网络算法和遗传算法对机床机构尺寸参数半径R与杆长L进行了综合优化。结果表明优化后的综合性能得到了提高。Inverse kinematics equations were established for a 3-P- （2U-2S） parallel mechanism of machine tool, which solved for its workspace. By calculating the Jacobian matrix condition number, the condition index of kinematics properties of the parallel mechanism was obtained. By taking the workspace and Global Condition Index （GCI） as the evaluation index, with using of BP Neural network algorithm and genetic algorithm （ GA ）, structure size parameters of radius R and rod length L （R/L） of the machine tool mechanism were comprehensively optimized. The results show that the performance of the parallel mechanism has been !reproved after optimization.

关 键 词：并联机构 工作空间 条件数 遗传算法 参数优化 

分 类 号：TH112[机械工程—机械设计及理论]