Abstract
0n the basis of analyzing BOF steelmaking characteristics, a prediction model and control model based on neural network were established. Taking endpoint temperature and endpoint carbon content as control target, oxygen-blown volume and added coolant were calculated, then endpoint control of convert steelmaking was realized. Simulation results show that the simulation result of endpoint temperature and carbon content are satisfying and control strategy is very effective. The application results demonstrate the efficiency of the method.
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References
Li, G., Kong, J., Jiang, G.: Research and Application on Compound Intelligent Control System for Coke Oven Heating. Chinese Journal of Iron and Steel 43, 89–92 (2008)
Merriman, D.: Mass spectrometry for oxygen steelmaking control. Steel Times 225, 439–440 (1997)
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© 2011 Springer-Verlag Berlin Heidelberg
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Li, G., Kong, J., Jiang, G., Yang, J., Xie, L. (2011). Intelligent Control System of BOF Steelmaking. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_34
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DOI: https://doi.org/10.1007/978-3-642-19853-3_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19852-6
Online ISBN: 978-3-642-19853-3
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