The Experimental Modal Analysis of High Speed Machining Tool System Based on Integral Polynomial Recognition Method


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According to the principle of the experimental modal analysis, this study is based on tool system of the MIKRON UCP 710 numerical control machining center as test object for experimental modal analysis. Using the integral polynomial recognition method to identify the modal parameters (natural frequency, structural damping, and modal shape), and finally matching the results with the vector analysis method and the finite element simulation method. The results show that integral polynomial recognition method has higher precision than the vector analysis method to identify the multi-degree of freedom system; the experimental modal analysis can also obtain better modal parameters of the structure system, and a higher precision than the finite element simulation method. Obtained the MIKRON UCP 710 high-speed milling center tool system accurate modal parameters provides the necessary theoretical and experimental basis for the further study of the stability properties in the cutting processing of the high speed machining tool system.



Edited by:

Zhanqiang Liu, Yi Wan, Qinghua Song and Zhenyu Shi






F. Xiao et al., "The Experimental Modal Analysis of High Speed Machining Tool System Based on Integral Polynomial Recognition Method", Materials Science Forum, Vol. 723, pp. 159-163, 2012

Online since:

June 2012




[1] J. Liang and D.F. Zhao: Mod. Manuf. Eng. Vol. 139 (2006) No. 3, pp.139-141.

[2] H.T. Wu: J. Kunming Univ. Sci. Technol. Vol. 25 (2000) No. 2, pp.50-53.

[3] A.S.M.Y. Munsi, A.J. Waddell, and C.A. Walker: Mech. Syst. Signal Proce. Vol. 16 (2002) No. 2-3, pp.273-284.

[4] S. Vanlanduit, P. Verboven, P. Guillaume and J. Schoukens: J. Sound Vib. Vol. 265 (2003) No. 3, pp.647-661.

[5] W.W. Nie, G.C. Wang, C.G. Shen, Z.P. Song and G. Liu: Tool Eng. Vol. 44 (2010) No. 7, pp.33-36.

[6] D.B. Li: Experimental Modal Analysis and Application (Science Press, China 2001).

[7] J.X. Zheng, M.J. Zhang and Q.X. Meng: Meas. Control Technol. Vol. 26 (2007) No. 12, pp.28-31.

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