中国机械工程

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一种新的预测铣刀刀尖频响函数的方法

朱坚民; 何丹丹; 田丰庆; 赵全龙   

  1. 上海理工大学,上海,200093
  • 出版日期:2016-10-25 发布日期:2016-10-21
  • 基金资助:
    国家自然科学基金资助项目(50975179);上海市教委科研创新项目(11ZZ136);上海市科委科研计划资助项目(12DZ2252300) 

A New Prediction Method of Tool Point Frequency Response Function for Milling Cutters

Zhu Jianmin;He Dandan;Tian Fengqing;Zhao Quanlong   

  1. University of Shanghai for Science and Technology,Shanghai,200093
  • Online:2016-10-25 Published:2016-10-21
  • Supported by:

摘要: 为准确快速地预测铣刀刀尖点频响函数,提出一种基于逆响应耦合子结构分析(IRCSA)法辨识刀柄-刀具结合面参数的刀尖点频响函数预测方法。该方法通过建立计算刀柄末端频响函数矩阵和刀尖点频响函数矩阵的数学模型,利用逆响应耦合子结构分析法求取随频率变化的刀柄-刀具结合面参数。通过Cuckoo search算法及有限元分析确定刀尖点频响函数中对刀柄-刀具结合面复刚度矩阵变化最为敏感的固有频率,取该频率对应的结合面参数为刀柄-刀具结合面复刚度矩阵的辨识结果,由此计算出刀尖点频响函数。通过硬质合金圆柱棒、2刃铣刀和4刃铣刀进行验证,对比了所提预测方法、Cuckoo search优化算法预测的刀尖点频响函数与实测值三者之间的差异,实验结果表明该预测方法预测的刀尖点频响函数的固有频率和实测固有频率的误差在5%以内,所用时间约为Cuckoo search优化算法的1%,达到了较高的预测精度,并且更加省时、简便。

关键词: 刀尖点频响函数, 逆响应耦合子结构分析(IRCSA), 结合面复刚度矩阵, Cuckoo search算法, 预测

Abstract: To predict tool point frequency response function of milling cutters accurately and rapidly, a new tool point frequency response function prediction method was proposed, which was based on IRCSA to identify joint parameters of holder-tool. Firstly, the joint parameters of holder-tool changing with the frequency were obtained by calculating frequency response function matrixes of holder end and tool point based on the mathematical models, and applying IRCSA. Secondly, the natural frequency of tool point frequency response function was determined, which was sensitive to variations of the complex stiffness matrixes of holder-tool joints by Cuckoo search algorithm and finite element analysis. At last, the joint parameters under the determined frequency were taken as the result of the complex stiffness matrix, which was used to predict the tool point frequency response function. To confirm the presented theory, a carbide cylindrical rod, 2 fluted milling cutter and 4 fluted milling cutter were taken as examples, and the predicted tool point frequency response functions based on the new method and Cuckoo search algorithm of them were compared with measured ones. It is experimentally demonstrated that the new method has high prediction precision and is time-saving, the errors between the natural frequencies of the predicted tool point frequency response functions based on the new method and measured ones are within 5%, and time the new method used is about 1% of the Cuckoo search algorithm used.

Key words: tool point frequency response function, inverse receptance coupling substructure analysis(IRCSA), complex stiffness matrix of holder-tool joint, Cuckoo search algorithm, prediction

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