Abstract
A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes.
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Blachnik, M., Wieczorek, T., Mączka, K., Kopeć, G. (2010). Identification of Liquid State of Scrap in Electric Arc Furnace by the Use of Computational Intelligence Methods. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_86
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DOI: https://doi.org/10.1007/978-3-642-17534-3_86
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