Abstract
Due to the complex nature (e.g., highly nonlinear, time varying, and spatially varying) of the laminar cooling process, accurate mathematical modeling of the process is difficult. This paper developed a hybrid model of the laminar cooling process by integrating Radial Basis Function (RBF) networks into the first principles dynamical model. The heat transfer coefficients of water cooling in the dynamical model were found by RBF networks. The developed model is capable of predicting the through-thickness temperature evolutions of the moving strip during the laminar cooling process. Experimental studies using real data from a hot strip mill show the superiority of the proposed model.
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References
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© 2006 Springer-Verlag Berlin Heidelberg
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Tan, M., Zong, X., Yue, H., Pian, J., Chai, T. (2006). Laminar Cooling Process Model Development Using RBF Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_124
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DOI: https://doi.org/10.1007/11760191_124
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
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