Moment Stability of Stochastic Regenerative Cutting Process

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Abstract:

The stochastic uncertainties of regenerative cutting process (RCP) are taken into consideration, and both cutting stiffness and damping coefficients are modeled as two stationary stochastic processes. The eigenvalue equations are established for the stability analysis of stochastic RCP, corresponding to the differential equations of the first and second order moments. Thus the stability analysis of stochastic RCP is transformed into that of the first two order moments. The influence of stochastic uncertainties on the cutting stability of RCP is discussed. The numerical experiments have verified that with the increase of stochastic uncertainties, the cutting stability boundary was shifted downwards significantly, and the number of lobes was also multiplied.

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Periodical:

Advanced Materials Research (Volumes 97-101)

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3038-3041

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March 2010

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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[1] S. A. Tobias: Machine Tool Vibration. (Blackie, Glasgow 1965).

Google Scholar

[2] Y. Altintas and E. Budak: Annals of CIRP, Vol. 44 (1995), No. 1, pp.357-362.

Google Scholar

[3] S. Jayaram, S. G. Kapoor and R. E. DeVor: ASME J. of Manufacturing Science and Engineering, Vol. 122 (2000), No. 3, pp.391-397.

Google Scholar

[4] M. A. Davies, J. R. Pratt, B. Dutterer, et al: ASME J. of Manufacturing Science and Engineering, Vol. 124 (2002), No. 2, pp.217-225.

Google Scholar

[5] T. Insperger, B. P. Mann, G. Stepan et al: Int. J. of Machine Tools and Manufacture, Vol. 43 (2003), No. 1, pp.25-34.

Google Scholar

[6] G. Totis: Int. J. of Machine Tools and Manufacture, Vol. 49 (2009), No. 3-4, pp.273-284.

Google Scholar

[7] E. Shamoto, and K. Akazawa: Annals of CIRP, Vol. 58 (2009), No. 1, pp.351-354.

Google Scholar

[8] X. Mao: Exponential stability of stochastic differential equations, (Marcel Dekker, New York 1994).

Google Scholar

[9] L. Arnold: Stochastic differential equations: theory and applications. (Wiley, New York 1974).

Google Scholar