• CN:11-2187/TH
  • ISSN:0577-6686

›› 2011, Vol. 47 ›› Issue (11): 125-133.

• 论文 • 上一篇    下一篇

基于响应面法的立式加工中心动静态多目标优化

姜衡;管贻生;邱志成;张宪民; 陈忠;许冠   

  1. 华南理工大学机械与汽车工程学院;佛山市南海中南机械有限公司
  • 发布日期:2011-06-05

Dynamic and Static Multi-objective Optimization of a Vertical Machining Center Based on Response Surface Method

JIANG Heng;GUAN Yisheng;QIU Zhicheng;ZHANG Xianmin;CHEN Zhong;XU Guan   

  1. School of Mechanical & Automotive Engineering, South China University of Technology Foshan Nanhai Zhongnan Machinery Co. Ltd.
  • Published:2011-06-05

摘要: 为了满足在保证加工中心初始动静态刚度的条件下达到整机轻量化的要求,提出基于质量和第一阶固有频率为目标函数的整机多目标优化设计方法。将有限元分析和模态试验相结合,测试和分析整机动态特性,确保有限元模型精度。通过中心复合设计的试验方法选取合适的结构有限元分析样本点,在ANSYS仿真软件中对样本点处的整机动静态特性进行计算和分析,根据获取的响应值建立反映结构设计输入与响应输出关系的二次多项式响应面模型。利用转移哈默斯利抽样技术,抽取均匀分布于设计空间中的样本点,并对其进行权衡排序,获得较优的初始种群。运用多目标遗传算法对加工中心整机质量和第一阶固有频率进行多目标优化,得到Pareto优化解集,在保证加工中心整机动静态性能不降的前提下,质量减轻6.58 %。结果表明,该方法具有较高的精度和较强的工程实用性。

关键词: 多目标优化, 响应面法, 优化设计, 有限元法

Abstract: In order to satisfy the performance requirement of the dynamic and static stiffness and light weight of a machining centre, a method of multi-objective optimization driven by the first natural frequency and mass is proposed. Modal parameters are identified by using a comprehensive approach based on modal test and finite element analysis. The appropriate structural finite element analysis samples in design space are selected by using the central composite design (CCD) experiment method. Quadratic polynomials are employed to construct response surface (RS) model, which reflects the relationship between design inputs and structural response outputs, according to the response outputs of these samples obtained by analyzing the dynamic and static characteristics of the machining centre at these samples with the software ANSYS. Well-distributed samples are generated in the design space by shifted Hammersley sampling method. The prominent points are selected as initial samples. The goal of getting higher first natural frequency and lighter weight is reached and the Pareto optimal solution set is obtained by the multi-objective genetic algorithm in the optimization. Through the optimization, the mass of the machining center is decreased by 6.58 % under the condition of ensuring the dynamic and static performance. The results show the high precision and strong engineering practicability of the proposed optimization method.

Key words: Finite element method, Multi-Objective optimization, Optimization design, Response surface methodology

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