基于改进NSGA-Ⅱ算法的箱形伸缩臂多目标优化设计  

Multi-target optimal design for box telescopic boom based on improved NSGA-Ⅱ algorithm

作　　者：王卫辉 刘涛 袁仁武 鹿飞 

机构地区：[1]第二炮兵工程大学,西安710025

出　　处：《起重运输机械》2014年第11期5-9,共5页Hoisting and Conveying Machinery

摘　　要：从初始群体产生及交叉算子两个方面对带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)进行改进,对伸缩臂进行应力及挠度变形分析,得出应力及应变云图,以确保伸缩臂强度、刚度满足要求。以伸缩臂截面几何参数为设计变量,伸缩臂稳定性及自重为优化目标,利用i SIGHT软件将改进的NSGA-Ⅱ算法与Ansys有限元分析集成,以QY20汽车起重机伸缩臂为例,对起重机箱形伸缩臂进行多目标优化设计,得出Pareto前沿解,并与优化前的截面参数进行对比,验证了该算法的可行性。The rapid non-dominated sorting genetic algorithm （NSGA-Ⅱ）with elitist strategy is improved in the as-pects of generation of initial population and crossover operator.The stress and deflection deformation analysis is performed for the telescopic boom to get the stress and strain cloud picture,in order to guarantee the telescopic boom meets the strength and rigidity requirements.With the geometrical parameters of telescopic boom cross-section as the design variable, its stability and self-weight as optimal objective,the improved NSGA-Ⅱalgorithm is integrated with Ansys finite element a-nalysis by iSIGHT software.With the telescopic boom of QY20 truck crane as an example,the multi-target optimal design is performed for box-type telescopic boom of the crane,to get Pareto leading-edge solution which is compared with the cross-section parameter before optimization,proving feasibility of the algorithm.

关 键 词：汽车起重机 遗传算法 伸缩臂 多目标优化 

分 类 号：TH213.6[机械工程—机械制造及自动化]