Predicting Tool Point FRF by RCSA in High Speed Milling

Kun Long Wen; Hou Jun Qi

doi:10.4028/www.scientific.net/AMR.1006-1007.398

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1006-1007Predicting Tool Point FRF by RCSA in High Speed...

Predicting Tool Point FRF by RCSA in High Speed Milling

Abstract:

Tool point frequency response function (FRF) is the key parameters to predict the milling stability in high-speed milling. Receptance coupling substructure analysis (RCSA) is described to predict the tool point FRF. The major difficulties in RCSA are the identification of joint connection parameters and the obtaining of FRFs of substructure. This paper separation of the milling system into three substructures: the machine-spindle-holder taper, the extended holder-tool shank, and the tool extended portion. Develop the connection model compose of linear and rotational springs and dampers. Determine the substructure FRF by measurement and Euler-Bernoulli beam model. Tool point FRF is obtained by coupling the substructure FRFs through the connection model by RCSA.

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Periodical:

Advanced Materials Research (Volumes 1006-1007)

Pages:

398-402

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1006-1007.398

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Online since:

August 2014

Authors:

Kun Long Wen*, Hou Jun Qi

Keywords:

Frequency Response Function, High Speed Milling, Receptance Coupling Substructure Analysis

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References

[1] Y. Altintas, Manufacturing Automation – Metal Cutting Mechanics, Machines Tool Vibrationand CNC Design, Cambridge University Press, (2000).

Google Scholar

[2] T. L. Schmitz, M. A. Davies andM. D. Kennedy, High-speed machining frequency response prediction for process optimization, Proceedings of the 2ndInternational seminar on Improving Machine Tool Performance, (2000).

Google Scholar

[3] T. L. Schmitz, Predicting high-speed machining dynamics by substructure analysis, Annals of CIRP, 2000, 303-308.

DOI: 10.1016/s0007-8506(07)62951-5

Google Scholar

[4] T. L. Schmitz, M. A. Davies andM. D. Kennedy, Tool Point Frequency Response Prediction for High-Speed Machining by RCSA, Journal of Manufacturing Science and Engineering, 2001, 123: 700-707.

DOI: 10.1115/1.1392994

Google Scholar

[5] S. S. Park, Y. Altintas andM. Movahhedy, Receptance coupling for end mills, International Journal of Machine Tools & Manufacture, 2003, 43: 889-896.

DOI: 10.1016/s0890-6955(03)00088-9

Google Scholar

[6] G. Scott Duncan andT. L. Schmitz, An Improved RCSA Model for Tool Point Frequency Response Prediction, in: Proceedings of the 23rd International Modal Analysis Conference, 30 January-3 February 2005, Orlando, FL (on CD).

Google Scholar

[7] ZHANG J, SCHMITZ T, ZHAO W, et al. Receptance Coupling for Tool Point Dynamics Prediction on Machine Tools, Chinese Journal of Mechanical Engineering-English Edition, 2011, 24(3): 340.

DOI: 10.3901/cjme.2011.03.340

Google Scholar

[8] T. L. Schmitz, K. S. Smith. Machining Dynamics, Springer Science, LLC, New York, (2009).

Google Scholar