Roll-Force and Torque Coefficients for Hot-Strip Steel Mill

1960 ◽  
Vol 82 (3) ◽  
pp. 683-688
Author(s):  
B. N. Garudachar ◽  
H. A. Peterson

This paper provides results of an analytical and computer investigation to determine the numerical coefficients involved in the roll-force and roll-torque equations pertaining to a single stand in a multistand, tandem, steel rolling mill. To the authors’ knowledge, such information has not appeared in the literature to date. The coefficients for a typical hot mill are compared with those obtained for a typical cold mill. The principles of gage control are discussed. The theories on flat-strip rolling are reviewed briefly.

2021 ◽  
pp. 100245
Author(s):  
Shuhong Shen ◽  
Denzel Guye ◽  
Xiaoping Ma ◽  
Stephen Yue ◽  
Narges Armanfard

2019 ◽  
Vol 59 (9) ◽  
pp. 1604-1613 ◽  
Author(s):  
Zhenhua Wang ◽  
Dianhua Zhang ◽  
Dianyao Gong ◽  
Wen Peng

Author(s):  
D. Ll. Davies ◽  
J. Watton ◽  
Y. Xue ◽  
G. A. Williams

With increasing international competition in steel production mainly from developing nations, it is important for steel plants to keep up to date with new technologies, and continuously improve on current practices and manufacturing techniques to remain competitive. This paper looks specifically at improvements to the hot rolling mill downcoilers, which is where the strip is coiled at the end of the rolling process. Hydraulic and pneumatic technology is combined to give accurate position control of guide wrappers that aid the initial coiling process. The paper presents an experimental test rig, using an actual wrapper guide, constructed to evaluate the specific design approach.


2004 ◽  
Vol 18 (6) ◽  
pp. 972-978 ◽  
Author(s):  
Young Hoon Moon ◽  
I Seok Jo ◽  
Chester J. Van Tyne

1980 ◽  
Vol 102 (2) ◽  
pp. 118-122 ◽  
Author(s):  
A. A. Desrochers ◽  
G. N. Saridis

This paper presents roll force control methods to be used with the predictive force setup model of the finishing stands in a hot steel rolling mill. Current mill practices achieve a desired strip gauge by using a predictive force model to setup the roll gaps on the finishing stands. At any time before the steel enters the first finishing stand a human operator may modify the roll gap settings if it is felt that under the present conditions the force predicted by the setup model is going to be unacceptable. In this paper, the decision process of the operator is modelled by pattern recognition methods to obtain this extra degree of feedforward control. In addition, feedback control is provided from one steel run to the next by an adaptive controller which uses a linear reinforcement learning scheme to adjust its parameters. Results are presented from actual mill data.


2016 ◽  
Vol 23 (12) ◽  
pp. 1268-1276 ◽  
Author(s):  
Wei-gang Li ◽  
Chao Liu ◽  
Ning Feng ◽  
Xi Chen ◽  
Xiang-hua Liu

Sign in / Sign up

Export Citation Format

Share Document