Modelling of Friction Coefficient in Cold Strip Rolling

Abstract:

The variation of the friction in the roll bite is of great importance in cold strip rolling. The main interest of the paper is to model the friction coefficient in the roll bite during cold rolling. The deformation resistance of the rolled products and friction coefficient in the roll bite were determined simultaneously by minimizing the error of the measured and calculated rolling forces based on nonlinear least squares optimization algorithm. The neural network was introduced to further improve the accuracy of friction coefficient calculation in cold strip rolling. The results already obtained shows that friction decreases with roll wear, and the lower the rolling speed, the higher is the friction.

• Periodical: Materials Science Forum (Volumes 505-507)
• Pages: 1285-1290
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.505-507.1285
• Online since: January 2006
• Authors: A. Kiet Tieu, Hong Tao Zhu, Cheng Lu, C. You, Zheng Yi Jiang, Giovanni D'Alessio
• Keywords: Cold Rolling, Friction, Neural Network (NN), Optimization

References

[1] A.K. Tieu, and Y.J. Liu: Tribol. Int. Vol. 37 (2004), p.177.

[2] E.B. Li, A.K. Tieu, and W. Y D. Yuen: J. Mater. Process. Technol. Vol. 133 (2003), p.348.

[3] W.Y.D. Yuen: Proc. ACAM01, Melbourne, Australia, 927 (1996).

[4] W.Y.D. Yuen, Y. Popelianski and M. Prouten: Proc. MWSPC37, Hamilton, Canada, 33 (1996).

[5] J. Larkiola, P. Myllykoski, J. Nylander and A.S. Korhonen: Materials Processing in the Computer Age (T.M.S., USA 1994).

[6] J. Yang: Mathematical model of rolling process (Metallurgical Industry Press, Beijing 1983).

[7] D.R. Bland and H. Ford: Proc. Instn. Mech. Engrs. Vol. 159 (1948), p.144.

[8] M.D. Stone: Iron Steel Eng., Vol. 30 (1953), p.61.

[9] N.A. Fleck and K.L. Johnson: Int. J. Mech. Sci. Vol. 29 (1987), p.507.

[10] J.H. Hitchcock: ASME Res. Publ., Appendix I, (1935).

[11] T.F. Coleman and Y. Li: SIAM Journal on Optimization Vol. 6 (1996), p.418.