摘要
为了提高梁柱材钻铣刨加工中心的综合性能,本文以其中具有X,Y方向插补运动的刀架为研究对象,进行轻量化设计。对刀架的质量进行两次优化:第一次使用拓扑算法优化,以最大刚度为目标函数,应力、变形为约束,质量为响应约束,建立拓扑优化模型进行优化;第二次使用MOGA算法在拓扑优化的基础上进行优化,建立拓扑优化刀架的重构模型,验证力学性能与低阶固有频率,选择优化设计变量,设计CCD(Central composite design)试验获得初始样本点,选取5个验证点与Kriging模型的预测值进行拟合,根据Kriging模型建立局部灵敏度较高设计变量的响应面模型,获得设计变量对应力、变形、质量直观的影响程度,利用MOGA算法建立优化模型,寻找最优解。试验结果表明:在满足强度的条件下,经过两次质量优化设计,刀架质量减小了14.48%。
In order to improve the comprehensive performance of beam-column material drilling and milling machining center,the tool rest with X and Y direction interpolation movement as the object is taken to carry out the lightweight design.The tool rest mass was optimized twice.In the first optimization,topology algorithm was used to establish a topology optimization model with the maximum stiffness as the objective function,stress and strain as constraints,and mass as response constraints.For the second time,MOGA algorithm was used to optimize the tool rest on the basis of topology optimization,and a topology optimization tool rest reconstruction model was established to verify mechanical properties and low order natural frequencies.Optimization design variables were selected,and CCD(Central composite design)experiment was designed to obtain initial sample points.Five verification points were selected to fit the predicted values via Kriging model.A response surface model with high local sensitivity was established according to Kriging model to obtain the influence of the design variables on the stress,deformation and mass.An optimization model was established by using the MOGA algorithm to find the optimal solution.The test results show that the tool rest mass is reduced by 14.48%after two quality optimization designs under the satisfying strength.
作者
杨春梅
马亚强
刘彤彬
丁禹程
宋文龙
YANG Chunmei;MA Yaqiang;LIU Tongbin;DING Yucheng;SONG Wenlong(School of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,China)
出处
《机械科学与技术》
CSCD
北大核心
2024年第9期1590-1599,共10页
Mechanical Science and Technology for Aerospace Engineering
基金
中央高校基本科研业务费专项(2572020DR12)
黑龙江省重点研发项目(GA21A405)。