重型车床床身性能分析及多目标参数优化  

Performance Analysis and Multi-Objective Parameter Optimization of Heavy Lathe Bed

作　　者：杨志贤 洪后紧 顾寄南[1] YANG Zhi-xian;HONG Hou-jin;GU Ji-nan(Manufacturing Information Engineering Research Center,Jiangsu University,Jiangsu Zhenjiang212013,China)

机构地区：[1]江苏大学制造业信息化研究中心,江苏镇江212013

出　　处：《机械设计与制造》2020年第5期88-91,95,共5页Machinery Design & Manufacture

基　　金：江苏省重大科技成果转化项目(BA2015026)。

摘　　要：以重型卧式车床床身为研究对象,为满足床身在静刚度不降低条件下达到轻量化、动静态性能好这一要求,提出以质量、最大变形和低阶固有频率为目标的优化设计方法。通过正交实验法建立了床身低阶固有频率、最大变形和质量关于筋板厚度的响应面模型,并对模型的准确性进行了验证。运用带有非支配排序遗传算法(NSGA-Ⅱ)对床身进行多目标优化求解,得到了Pareto最优解集。在此基础之上,采用基于信息熵赋权的多目标灰靶决策算法对Pareto解集进行优选。通过对最终方案进行有限元分析,优化后的床身动静态性能略有提高,质量减轻了604kg。具体算例表明,该方法具有实用性。Taking the heavy horizontal lathe bed as the research object.In order to meet the requirements of the lathe bed to achieve the lightweight,dynamic and static performance under the condition of not decreasing the static stiffness,an optimization design method with the objective of quality,maximum deformation and low-order natural frequency is proposed.The response surface model of the low order natural frequency,maximum deformation and mass of the bed body is established by the orthogonal experiment method,and the accuracy of the model is verified. By using the genetic algorithm(NSGA-Ⅱ)with non-dominated ordering,the multi-objective optimization of the bed is carried out andthe Pareto optimal solution set is obtained. On this basis,the multi-objective grey target decision algorithm with information entropy weighting isapplied to choose the final scheme from the Pareto solution set. Through the finite element analysis of the final scheme,the dynamic and static characteristics of the optimized bed slightlyimproved,the quality is reduced by 604 kg. The concrete example shows that the method has strong practicability.

关 键 词：灰靶决策 遗传算法 正交实验 车床床身 多目标优化 

分 类 号：TH16[机械工程—机械制造及自动化] TG502[金属学及工艺—金属切削加工及机床]