基于Kriging模型与NSGA-Ⅱ算法的堆垛机结构优化设计  

Optimization of Stacker Structure Based on Kriging Model and NSGA-Ⅱ Algorithm

作　　者：杨瑞刚[1] 高林 董青[1] 徐格宁[1] YANG Rui-gang;GAO Lin;DONG Qing;XU Ge-ning(School of Machinery and Electronics Engineering,Taiyuan University of Science and Technology,Shanxi Taiyuan 030024,China)

机构地区：[1]太原科技大学机械工程学院,山西太原030024

出　　处：《机械设计与制造》2022年第5期298-304,共7页Machinery Design & Manufacture

基　　金：“十三五”国家重点研发计划—港口等领域典型起重机械设计制造与服役过程风险防控关键技术研究(2017YFC0805703)。

摘　　要：针对双高双立柱式堆垛机结构设计时存在的结构非线性与设计参数响应值之间复杂的隐式关系。采用三维参数化建模和最佳填充样本空间(OSF)进行试验设计,利用Kriging模型建立双高双立柱式堆垛机设计参数和最大应力、最大位移和质量之间的映射关系,通过精英保留策略快速非支配排序多目标遗传算法(NSGA-Ⅱ),实现堆垛机结构尺寸、箱型梁壁厚的最佳寻优化方案,以满足强度、刚度、稳定性和优化设计目标。结果表明,采用该方法能够有效提高双高双立柱式堆垛机的静态结构优化设计精度和效率。The complex implicit relationship between the structural non-linearity and the design parameter response value of the double-height and double-column stacker structure design. Three-dimensional parametric modeling and optimal filling sample space(OSF)were used for experimental design,and the Kriging model was used to establish the mapping relationship between the design parameters of the double-height and double-column stacker and the maximum stress,maximum displacement,and mass,retained by the elite Strategy fast non-dominated sorting multi-objective genetic algorithm(NSGA-Ⅱ)to achieve the optimal search and optimization of stacker structure size and box beam wall thickness to meet strength,stiffness,stability and optimization design goals. The results show that the static structure optimization design precision and efficiency of the double-high double-column stacker can be effectively improved by this method.

关 键 词：参数化建模 最佳填充样本空间 KRIGING模型 多目标遗传算法 

分 类 号：TH16[机械工程—机械制造及自动化] TB246[一般工业技术—工程设计测绘]