优化过程知识引导的斗杆结构智能遗传寻优方法  

Optimal Process Knowledge-Based Genetic Optimization Algorithm for Excavator Stick

作　　者：张洋梅 沈振辉[1] 花海燕 ZHANG Yangmei;SHEN Zhenhui;HUA Haiyan(School of Enginnering,Fujian Jiangxia University,Fuzhou,Fujian 350108;School of Mechanical and Automative Engineering,Fujian University of Technology,Fuzhou,Fujian 350108)

机构地区：[1]福建江夏学院工程学院,福建福州350108 [2]福建工程学院机械与汽车工程学院,福建福州350108

出　　处：《武夷学院学报》2018年第9期45-51,共7页Journal of Wuyi University

基　　金：2017年福建省中青年教师教育科研项目(JAT170613);福建工程学院科研启动基金项目(GY-Z14075)

摘　　要：针对现有挖掘机斗杆结构智能数值寻优方法,未能提取利用优化群体优化过程中产生的目标知识及约束知识指导数值寻优,致使结构数值寻优效率较低,常收敛于局部最优解等问题,提出一种基于优化过程知识的斗杆结构遗传寻优方法,构建优化过程知识引导的群体选择算子、个体综合状态判断算子、群体交叉算子和群体变异算子,以充分利用优化过程知识指导斗杆结构遗传寻优过程。以中小型挖掘机耳板分离式斗杆结构为例,对比三种不同斗杆结构数值寻优结果,证实了优化过程知识引导的斗杆结构遗传寻优方法的可行性与高效性。In view of the deficiencies existing in cun＇ent knowledge-based global numerical optimization for excavator stick such as the insufficiency in acquiring and utilizing optimal process knowledge to guide the global numerical optimization for stick, the easily falling in local optimal solution and so on, the optimal process knowledge-based genetic optimization algorithm for excavator stick is proposed. By establishing the selecting operator, crossover operator and mutation operator based on optimal process knowledge to realize the sufficiency in utilizing optimal process knowledge to guide the genetic intelligent optimization algorithm for stick. The structural optimization of ear-plate stick for medium hydraulic excavator is taken as example, which demonstrates that the genetic optimization algorithm based on opti-mal process knowledge for stick is feasible and efficacious.

关 键 词：挖掘机斗杆 遗传算法 优化过程知识 结构优化 

分 类 号：TH122[机械工程—机械设计及理论]