东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (12): 1725-1728.DOI: -

• 论著 • 上一篇    下一篇

热轧带钢轧后冷却控制及其自学习方法

刘伟嵬;李海军;王昭东;王国栋;   

  1. 东北大学轧制技术及连轧自动化国家重点实验室;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 出版日期:2010-12-15 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    “十一五”国家科技支撑计划项目(2006BAE03A08)

Cooling temperature control of hot rolled steel strip and its self-learning

Liu, Wei-Wei (1); Li, Hai-Jun (1); Wang, Zhao-Dong (1); Wang, Guo-Dong (1)   

  1. (1) The State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-12-15 Published:2013-06-20
  • Contact: Liu, W.-W.
  • About author:-
  • Supported by:
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摘要： 热轧带钢轧后冷却过程中卷取温度的控制精度是保证带钢表面质量和板形良好的一个关键因素,因此温度控制精度的核心是冷却过程控制模型的建立,同时新的数学模型应该具有自学习功能以提高控制精度.以此为出发点,建立了具有非线性结构特征的热轧带钢冷却过程控制的数学模型,并对新模型的自学习能力进行了研究,使该模型能够不断地修正其关键参数以提高温度控制精度,从而增强了模型的自适应性.通过对该冷却过程数学模型的现场实际应用,验证了该冷却数学模型的卷取温度控制能够达到较高的精度,为提高带钢产品质量奠定了基础.

关键词: 冷却过程, 数学模型, 卷取温度, 自学习, 热轧带钢

Abstract: Control precision of coiling temperature is one of the key factors influencing on the strip quality/shape during the cooling process of hot rolled steel strip. The temperature control precision is therefore the core of the mathematical model to control cooling process and, at the same time, the mathematical model should serve the function of self-learning to improve the temperature control precision. A mathematical model with nonlinear structural characteristics was developed to control the cooling process. Analyzing its self-learning ability, the model enables the key parameters to be corrected uninterruptedly so as to improve the temperature control precision and adaptability of the model. The in-situ application results verified that the mathematical model developed can provide high control precision of coiling temperature, thus laying a foundation for improving steel strip quality.

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