• DocumentCode
    2659133
  • Title

    Application of artificial neural network in judging the end point of the zinc fuming furnace

  • Author

    Shouming, Zhang ; Yunsheng, Zhang

  • Author_Institution
    Fac. of Inf. Eng. & Autom., Kuming Univ. of Sci. & Technol., Kuming
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    469
  • Lastpage
    471
  • Abstract
    For a long time the judgment of zinc fuming furnace´s smelting end point has primarily depended on the operator´s observation on flames through their naked eyes. The accuracy of the judgment is easily and strongly influenced by subjective factors, which makes it difficult to guarantee the stability of the product quality and restricts the enhancement of production efficiency. Therefore, this paper put forward a method based on artificial neural network to discriminate flames and judge the end point automatically. Utilizing this method, a computer judging system has been set up in YUNNAN CHIHONG ZINC&GERMANIUM Co., ltd, and can effectively discriminate zinc fuming furnace´s end point.
  • Keywords
    electrical engineering computing; furnaces; neural nets; zinc; artificial neural network; product quality; production efficiency; smelting end point; stability; subjective factors; zinc fuming furnace; Artificial neural networks; Costs; Eyes; Fires; Furnaces; Heating; Production; Slag; Temperature; Zinc; Artificial Neural Network; Judging the End Point; Zinc Fuming Furnace;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2008. CCC 2008. 27th Chinese
  • Conference_Location
    Kunming
  • Print_ISBN
    978-7-900719-70-6
  • Electronic_ISBN
    978-7-900719-70-6
  • Type

    conf

  • DOI
    10.1109/CHICC.2008.4605093
  • Filename
    4605093