Neural modeling helps the BOS process to achieve aimed end-point conditions in liquid steel

Engineering Applications of Artificial Intelligence

Volumn 19, Issue 1, 2006, Pages 9-17

  Fileti, A M Frattini ^a   Pacianotto, T A ^a   Cunha, A Pitasse ^b  

^a UNIVERSITY OF CAMPINAS   (Brazil)

^b Companhia Siderúrgica Nacional ^*  (Brazil)

Author keywords

Basic oxygen steel making; BOS process; LD converter; Neural network; Steel refining

Indexed keywords

CARBON; COMPOSITION; COOLANTS; NEURAL NETWORKS; OSCILLATIONS; OXYGEN; RAW MATERIALS; REFINING;

BASIC OXYGEN STEEL-MAKING (BOS); BOS PROCESS; LD CONVERTERS; STEEL REFINING;

STEEL;

EID: 29144456822     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2005.06.002     Document Type: Article

References (10)

1. B. Barros Neto, I.S. Scarminio, and R.E. Bruns Como fazer experimentos - Pesquisa e desenvolvimento na indústria 2001 State University of Campinas Inc. Brazil
2. I.J. Cox, R.W. Lewis, R.S. Ransing, H. Laszczewski, and G. Berni Application of neural computing in basic oxygen steelmaking Journal of Materials Processing Technology 120 2002 310 315
3. Demuth, H., Beale, M., 2002. Neural Network Toolbox User's Guide for Use with MATLAB® The Mathworks Inc., Version 4, Reading, In: Hagan, M. (Eds.), Backpropagation (Chapter 5).
4. F.D. Foresee, and M.T. Hagan Gauss-Newton approximation to Bayesian learning Proceedings of IJCNN 1997 1930 1935
5. D.M. Himmelblau Applications of artificial networks in chemical engineering Korean Journal of Chemical Engineering 17 4 2000 373 392
6. F. Kostersitz Integrated automation system for operating the LD converters at the LD steel plant of Voest-Alpine, Linz, Austria European Oxygen Steelmaking Congress, Dusseldorf 1993 102 106
7. Neto, L.C., 1981. End-blow model for control of LD converters and statistic analysis of its performance. Master's Thesis, Federal University of Minas Gerais, Brazil.
8. H. Ping, L. Liu, Y. Lihong, H. Zhigang, D. Rong, X. Jingbo, C. Wei, T. Yisheng, Y. Chenghuan, and L. Fengxi Combining intelligent and mathematical models for BOS control at WISCO Steel Times International 27 8 2003 31 32
9. V.R. Radhakrishnan, and A.R. Mohamed Neural networks for the identification and control of blast furnace hot metal quality Journal of Process Control 10 2000 509 524
10. M. Schlang, E. Broese, B. Feldkeller, O. Gramckow, M. Jansen, T. Poppe, C. Schäffner, and G. Sörgel Neural networks for process control in steel manufacturing Proceedings of ICASSP 1 1997 155