Dynamic modeling and parameter updating of machine tool spindle system based on response surface methodology and genetic algorithm

被引:0
|
作者
Chen C.-H. [1 ]
Yao G.-X. [1 ]
Jin T.-T. [1 ]
Shen G.-X. [1 ]
Yu L.-J. [1 ]
Tian H.-L. [1 ]
机构
[1] Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun
关键词
dynamics analysis; Key words; multi-objective genetic algorithm; response surface; spindle system;
D O I
10.13229/j.cnki.jdxbgxb20210311
中图分类号
学科分类号
摘要
Considering that the simplified processing in the process of establishing the dynamic model of the spindle system will lead to a large error,a dynamic modeling method based on response surface and genetic algorithm is proposed. Firstly,the dynamic model of the spindle system is established by considering the stiffness of the spindle-holder joint surface and the bearing support stiffness. Secondly,the main factors that affect the accuracy of dynamics analysis are developed by comparing the first three natural frequencies of the spindle system model with rigid and flexible connections. Then,sample points of contact stiffness are constructed based on the dynamics model of the spindle system,and the stiffness of the spindle-holder joint in the sample point is used as the input parameter,then the first,second,and third order natural frequency are used as the output parameters,and the non-parametric regression method is used to fit the response surface. The relative value of the determination coefficient and the root mean square error is used to test the accuracy of the response surface. The multi-objective genetic algorithm is used to update the stiffness of spindle-holder joint,which is used to update the dynamic model of the spindle system. Finally,a case study shows that the proposed method based on the fusion response surface methodology and optimization algorithm has higher analysis accuracy. © 2022 Editorial Board of Jilin University. All rights reserved.
引用
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页码:2278 / 2286
页数:8
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