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Milling stability prediction with simultaneously considering the multiple factors coupling effects—regenerative effect, mode coupling, and process damping

  • Yongjian Ji
  • Xibin Wang
  • Zhibing Liu
  • Hongjun Wang
  • Li Jiao
  • Lu Zhang
  • Tao Huang
ORIGINAL ARTICLE
  • 97 Downloads

Abstract

Chatter is a kind of self-excited vibrations which is related to regenerative effect, mode coupling effect, and process damping, etc. To predict milling chatter more accurately, a suitable dynamical model of milling process which can reflect the practical chatter mechanism should be obtained firstly. In this paper, a new milling dynamical model which simultaneously considers the regenerative effect, mode coupling effect, and process damping is established. Based on the new dynamical model and the updated full-discretization method (FDM), the coupling influences of regenerative effect, mode coupling effect, and process damping on the accurate of the stability lobe diagrams (SLDs) for up-milling and down-milling operations are investigated. A series of numerical simulation and experiments are carried out to verify the accuracy of the proposed milling dynamical model. The experiment results show that the mode coupling effect and process damping have great influences on the prediction of milling stability. The SLD which obtained by the new milling dynamical equation (considering the regenerative effect, mode coupling, and process damping) is more accurate than that which obtained by only considering the regenerative effect.

Keywords

Milling chatter prediction Mode coupling effect Regenerative effect Process damping Stability lobe diagrams 

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Notes

Acknowledgements

This work is jointly supported by the National Natural Science Foundation of China (Grant No. 51375055 and 51575055); The High-end CNC machine tools and basic manufacturing equipment Science and Technology Major Project of China (Grant No. 2015ZX04001002); Junior Fellowships for CAST Advanced Innovation Program (DXB-ZKQN-2016-003).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Yongjian Ji
    • 1
  • Xibin Wang
    • 1
  • Zhibing Liu
    • 1
  • Hongjun Wang
    • 2
  • Li Jiao
    • 1
  • Lu Zhang
    • 1
  • Tao Huang
    • 1
  1. 1.Key Laboratory of Fundamental Science for Advanced MachiningBeijing Institute of TechnologyBeijingPeople’s Republic of China
  2. 2.Key Laboratory of Modern Measurement and Control TechnologyBeijing Information Science and Technology UniversityBeijingPeople’s Republic of China

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