4.7 Article

An efficient decomposition-condensation method for chatter prediction in milling large-scale thin-walled structures

Journal

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 121, Issue -, Pages 58-76

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2018.11.013

Keywords

Flexible workpieces; Milling stability; In-process workpiece dynamics; Structural dynamic modification; Stability lobe diagram (SLD)

Funding

  1. National Natural Science Foundation of China [51705427, 11620101002, 51675440]
  2. National Key Research and Development Program of China [2017YFB1102800]
  3. China Postdoctoral Science Foundation [2017M610652]
  4. Fundamental Research Funds for the Central Universities [3102017ZY006]

Ask authors/readers for more resources

In this work, an efficient decomposition-condensation method is developed to predict the in-process workpiece (IPW) dynamics for chatter prediction in finishing and semi-finishing large-scale thin-walled structures. Considering the fact that the IPW dynamics is time-varying during the milling process, the IPW is decomposed into three components, namely the machined workpiece, the initial material to be removed and the removed material. The first component is kept unchanged, while the third component is subtracted from the second one. The initial material to be removed is updated by the structural dynamic modification technique to efficiently reveal the effect of material removal. Finite element models of the first two components are further condensed and coupled using component mode synthesis method to calculate the IPW dynamics. In this way, the model order of IPW is significantly reduced and the material removal can be simulated efficiently. The proposed method is finally integrated into a dynamic model for chatter prediction of the milling process. Two thin-walled pockets with planes and curved surfaces are investigated as typical cutting tests to verify the proposed method. It is shown that numerical results agree well with the experimental ones. For the same computing accuracy, the proposed method is observed to reduce the computational burden twice more than the existing methods for chatter prediction. (C) 2018 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available