Intelligent Method in the End-Point Control of BOF


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The design of BOF in Jiangyin Xingcheng Special Steel Co. Ltd is based on static and dynamic model. The BOF end-point carbon content and temperature are predicted by means of BP neural network. On basis of that, the consumption of material, output of static model, are regulated according to the prediction result. The shortcoming that the theory on static model is imperfect is overcome. The end-point hit rate is raised effectually in industrial practice.



Edited by:

Qi Luo




K. X. Peng et al., "Intelligent Method in the End-Point Control of BOF ", Applied Mechanics and Materials, Vols. 20-23, pp. 796-800, 2010

Online since:

January 2010




[1] Shu_ming Xie, Jun Tao, Tian_you Chai. in: BOF steelmaking endpoint control based on neural network, Control Theory & Application (2003), pp.903-907.

[2] H. W. Meyer & J. A. Glassgow: Iron Steel Eng., 43(1966), p.116.

[3] Jin_xia, Ning_de Jin, in: Static control predictive model for converter refining end-point. Steelmaking (2006), pp.45-48.