Hot metal temperature prediction by neural networks in the blast furnace

Authors

  • C. Cantera Centro Nacional de Investigaciones Metalúrgicas (CENIM), Consejo Superior de Investigaciones Científicas (CSIC). Madrid
  • J. Jiménez Centro Nacional de Investigaciones Metalúrgicas (CENIM), Consejo Superior de Investigaciones Científicas (CSIC). Madrid
  • I. Varela Centro Nacional de Investigaciones Metalúrgicas (CENIM), Consejo Superior de Investigaciones Científicas (CSIC). Madrid
  • A. Formoso Centro Nacional de Investigaciones Metalúrgicas (CENIM), Consejo Superior de Investigaciones Científicas (CSIC).Madrid

DOI:

https://doi.org/10.3989/revmetalm.2002.v38.i4.406

Keywords:

Blast furnace, Hot metal temperature, Neural networks, Prediction, Simulation,

Abstract


Based on a simplified model, the underlying temperature criteria is proposed as a method to study the temperature trends in a blast furnace. As, an application, a neural network able to forecast hot metal temperatures from 2 to 16 h in advance (with decreasing precision) has been built. This neural network has been designed to work at real time in a production plant.

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Published

2002-08-30

How to Cite

Cantera, C., Jiménez, J., Varela, I., & Formoso, A. (2002). Hot metal temperature prediction by neural networks in the blast furnace. Revista De Metalurgia, 38(4), 243–248. https://doi.org/10.3989/revmetalm.2002.v38.i4.406

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