A self-learning method for improving the hot-rolled plate shape

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Zhang, Chen^1 ; Liu, Ziying^1 ; Zhang, Changli^1 ; Li, Xudong^1 ; Wang, Qiuna^2

Shougang Research Institute of Technology, Beijing

100043, China^1

Beijing Shougang Co. Ltd, Qianan

064400, China^2

关键词: Control parameters;    Feedback compensation;    Multi standard;    Rolling conditions;    Rolling process;    Self-learning;    Shape set;    Steel production;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/2/022024/pdf
DOI  :  10.1088/1757-899X/452/2/022024

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

In the multi-standard rolling process of multi-steel production lines, frequent changes in specifications lead to slow self-learning and inaccurate learning, which makes the index of thickness deviation on plate out of target. To solve this problem, a quick self-learning method was designed and proposed. By calculating the crown deviation value of the current rolled steel strip, the bending roll force variation value and the plate shape feedback compensation value. The control parameters in the model are compensated accordingly to compensate for control deviations caused by changes in rolling conditions and the multi-standard steel. Experiments show that the rapid self-learning method can effectively improve the shape index.