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Artificial Neural Nets and Genetic Algorithms pp 86–88Cite as

A neural network model for blast furnace wall temperature pattern classification

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Abstract

A model for classification, visualization and interpretation of temperature distributions from the wall of the ironmaking blast furnace is presented. The model classifies the patterns using a self-organizing map and depicts the evolution of the distributions on the feature map, which is used as an operation diagram. The model has been implemented at the blast furnaces of a Finnish steelmaking company to improve the alertness of the operators and to help them to take appropriate control actions. The generic features of the models make it possible to apply the proposed classification method to different furnaces with only minor overhead for model tuning. Use of the classifications in operation diagrams is finally discussed.

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References

  1. Biswas, A.K.: Principles of Blast Furnace Ironmaking. Brisbane: Cootha Publishing House 1981.

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Author information

Authors and Affiliations

  1. Heat Engineering Laboratory, Åbo Akademi University, FIN-20500, Åbo, Finland

    Henrik Saxén

  2. TT Tieto Oy, Telecom, Kumpulantie 11, FIN-00521, Helsinki, Finland

    Leif Lassus

Authors
  1. Henrik Saxén
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  2. Leif Lassus
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© 1999 Springer-Verlag Wien

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Saxén, H., Lassus, L. (1999). A neural network model for blast furnace wall temperature pattern classification. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6384-9_15

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  • DOI: https://doi.org/10.1007/978-3-7091-6384-9_15

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83364-3

  • Online ISBN: 978-3-7091-6384-9

  • eBook Packages: Springer Book Archive

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