Prediction of the Hot Metal Silicon Content in the Blast Furnace

Beskardes A., Turkoglu S., ACI Ç.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.709-712 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2016.7495838
  • Basıldığı Şehir: Zonguldak
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.709-712
  • Çukurova Üniversitesi Adresli: Evet

Özet

Transforming of raw iron ore to liquid hot metal is operated at blast furnace which is one of the main unit of integrated iron and steel factories. Silicon content of liquid hot metal is the most important parameter concerning of product quality and blast furnace thermal condition. In this study a prediction model is established with artificial neural network's multilayer perceptron module by using 564 heat data of Iskenderun Iron & Steel Plant (ISDEMIR) Blast Furnace No 3. The silicon content of the next heat is predicted with accuracy of 83%.