• Title of article

    Long- and Short-Term Self-Learning Models of Rolling Force in Rolling Process Without Gaugemeter of Plate Original Research Article

  • Author/Authors

    Fu-wen ZHU، نويسنده , , Qing-liang ZENG، نويسنده , , Xianlei Hu، نويسنده , , Xi-an LI، نويسنده , , Xianghua Liu، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    5
  • From page
    27
  • To page
    31
  • Abstract
    Owing to a lack of gaugemeter and the variety of steel grades and standards in some plate mills, the long-and short-term self-learning models of rolling force based on gauge soft-measuring with high precision were brought up. The soft-measuring method and target value locked method were used in these models to confirm the actual exit gauge of passes, and thick layer division and exponential smoothing method were used to dispose the deformation resistance parameter, which could be calculated from the actual data of the rolling process. The correlative mathematical methods can also be adapted to self-learning with gaugemeter. The models were applied to the process control system of AGC (automatic gauge control) reconstruction on 2 800 mm finishing mill of Anyang steel and favorable effect was obtained.
  • Keywords
    Plate , self-learning , rolling force , soft measuring
  • Journal title
    Journal of Iron and Steel Research
  • Serial Year
    2009
  • Journal title
    Journal of Iron and Steel Research
  • Record number

    1235063