东北大学学报:自然科学版 ›› 2015, Vol. 36 ›› Issue (12): 1715-1718.DOI: 10.12068/j.issn.1005-3026.2015.12.010

• 材料与冶金 • 上一篇    下一篇

带钢热连轧换规格轧制力自学习优化

马更生, 彭文, 邸洪双, 张殿华   

  1. (东北大学 轧制技术及连轧自动化国家重点实验室, 辽宁 沈阳110819)
  • 收稿日期:2014-12-31 修回日期:2014-12-31 出版日期:2015-12-15 发布日期:2015-12-07
  • 通讯作者: 马更生
  • 作者简介:马更生(1984-),男,河北张家口人,东北大学博士研究生; 邸洪双(1958-),男,辽宁锦州人,东北大学教授,博士生导师; 张殿华(1963-),男,内蒙古赤峰人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(51074051).

Optimization of the Rolling Force Self-learning for Specifications Changing in the Hot Strip Rolling

MA Geng-sheng, PENG Wen, DI Hong-shuang, ZHANG Dian-hua   

  1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819, China.
  • Received:2014-12-31 Revised:2014-12-31 Online:2015-12-15 Published:2015-12-07
  • Contact: MA Geng-sheng
  • About author:-
  • Supported by:
    -

摘要: 热连轧带钢生产过程中,轧制力预报精度直接影响到带钢厚度的精度,而轧制力预报精度很大程度上依赖于轧制力自学习. 针对换规格时轧制力预报精度偏低的问题,通过对产生轧制力偏差的原因分析,引入基于钢种变形抗力的抛物线偏差曲线的概念、机架设备自学习系数和机架设备状态影响系数.现场实际应用效果表明:换规格后的首块钢的轧制力预报精度与传统方法相比,带钢头部的轧制力预报相对误差减小4%,满足自动厚度控制系统的控制要求,提高了带钢的产品质量,取得了良好的经济价值,适于工业推广.

关键词: 热连轧, 换规格, 轧制力自学习, 偏差曲线, 变形抗力

Abstract: In the hot strip rolling process, the prediction precision of the rolling force which is largely dependent on the rolling force self-learning directly affected the thickness precision of strips. In the view of the rolling force prediction precision decreased with the specifications changing, and through the analysis of the reasons for generating rolling force deviation, this paper introduced the concept of steel grade deformation resistance parabolic deviation curve, the equipment standers self-learning coefficient and equipment state effective coefficient to solve the problems. The practice application results showed that the relative error of the rolling force prediction for the first piece strip after changing specifications decreased by 4% compared with the conventional prediction method which satisfied the automatic thickness control system. The product quality of the strip was enhanced and good economic value was obtained, which indicated that the new prediction method was suitable for the industrial production promotion.

Key words: hot strip rolling, specifications changing, rolling force self-learning, deviation curve, deformation resistance

中图分类号: