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基于空间动力学优化的机床结构件质量匹配设计
引用本文:黄华,邓文强,李源,郭润兰.基于空间动力学优化的机床结构件质量匹配设计[J].浙江大学学报(自然科学版 ),2020,54(10):2009-2017.
作者姓名:黄华  邓文强  李源  郭润兰
作者单位:兰州理工大学 机电工程学院,甘肃 兰州 730000
基金项目:国家自然科学基金资助项目(51965037、51565030)
摘    要:提出基于整机空间动力学预测模型、以移动结构件质量为设计变量的多目标匹配设计方法. 基于机床移动件的工作行程构建整机工作空间,运用正交试验法进行空间位姿试验设计,建立整机空间固有频率预测模型;在工作空间内对机床进行动力学性能的灵敏度分析,识别动力学的最优位姿和最差位姿;以最差位姿机床固有频率为优化目标,采用多目标质量匹配法对移动部件的质量进行最佳分布设计;重新计算优化后机床的固有频率,通过频率响应分析,比较优化前、后机床在最差和最优位姿下的动力学性能. 结果表明,经过多目标质量匹配优化后,机床的固有频率得到了提高,刀尖节点的最大频响振幅明显降低,机床的整机动力学性能有了较大程度的改善.

关 键 词:空间位姿  预测模型  动态特性  多目标优化  质量匹配  

Mass matching design of machine tool parts based on spatial dynamics optimization
Hua HUANG,Wen-qiang DENG,Yuan LI,Run-lan GUO.Mass matching design of machine tool parts based on spatial dynamics optimization[J].Journal of Zhejiang University(Engineering Science),2020,54(10):2009-2017.
Authors:Hua HUANG  Wen-qiang DENG  Yuan LI  Run-lan GUO
Abstract:A multi-objective matching design method based on the whole machine space dynamics prediction model was proposed by taking the moving structure mass as design variables. The whole machine workspace was constructed based on the working stroke of the moving parts of the machine tool. Then the orthogonal test method was used to design the spatial pose, and the prediction model of the spatial natural frequency was established. The sensitivity analysis of the machining path was conducted in the workspace. The best and worst position was identified. Then the optimal distribution of the mass of moving parts was designed by multi-objective mass matching method by taking the natural frequency of the machine tool with the worst position as the optimization objective. The natural frequency of the optimized machine tool was calculated. The dynamic characteristics of the best and worst position before and after optimization were analyzed and compared. Results show that the natural frequency of the machine tool was improved with the optimization of multi-objective mass matching, and the maximum frequency response amplitude of the tool tip was significantly reduced. The dynamic performance of the machine tool was greatly improved.
Keywords:spatial pose  prediction model  dynamic characteristics  multi-objective optimization  mass matching  
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