An On-Line Model to Calculate the Strip Temperature at Run-Out Table of Tisco’s Hot Strip Mill

2003 ◽  
Author(s):  
A. Mukhopadhyay ◽  
S. Sikdar ◽  
S. Sen
Keyword(s):  
Mechanical Properties ◽  
Mathematical Model ◽  
Hot Strip Mill ◽  
Water Cooling ◽  
Coiling Temperature ◽  
Line Model ◽  
Finite Difference Technique ◽  
Hot Strip ◽  
On Line ◽  
Explicit Finite Difference

A Mathematical model has been developed to predict the temperature profile of the strip during water-cooling on the Run-out Table (ROT) of the Hot Strip Mill (HSM). This work describes the development and implementation of the model at Tisco’s HSM. The model has been developed using Explicit Finite Difference technique to predict the coiling temperature (CT). The model has been implemented successfully after having been validated with the actual coiling temperature (CT) for several thousand coils. A number of grades of steel with various thicknesses have been tested with this on-line model and the agreement of actual CT with the predicted ones was found very good. The on-line model is used to calculate the cooling rates at different segments of the strip that are used to obtain microstructure and mechanical properties.

Coiling Temperature Prediction and Application Based on Genetic-Neural Network on Hot Strip Mill

2013 ◽  
Vol 448-453 ◽  
pp. 3417-3420 ◽  
Author(s):  
Tie Jun Sun ◽  
Wei Dong Yang ◽  
Hai Gao ◽  
Hong Tao Mi
Keyword(s):  
Neural Network ◽  
Hot Strip Mill ◽  
Hot Strip Rolling ◽  
Coiling Temperature ◽  
Strip Rolling ◽  
Control Precision ◽  
Hot Strip ◽  
On Line ◽  
Genetic Neural Network ◽  
Coiling Temperature Control

Coiling temperature control (CTC) is very important to the quality of the strip steel in Hot Strip Rolling Mill. In the paper, genetic algorithm and neural network method to predict coiling temperature on hot strip mill were put forward. The genetic-neural network was trained and checked with actual production data. The result indicates that the method can real-time predict the strip coiling temperature. The on-line prediction model and step track method has been put into use. The result shows that the method can settle lag influence in feedback control and the CTC control precision is improved greatly.

Research for Coiling Temperature Control System and Mathematical Model on Hot Strip Mill

2011 ◽  
Vol 411 ◽  
pp. 274-278
Author(s):  
Lei Zhang ◽  
Hai Gang Xu ◽  
Chao Zhang ◽  
Chao Wei Duan
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Temperature Control System ◽  
Hot Strip Mill ◽  
Engineering Practice ◽  
Steel Mill ◽  
Laminar Cooling ◽  
Coiling Temperature ◽  
Strip Steel ◽  
Hot Strip

Laminar Cooling is an indispensable part of hot strip steel mill. Based on the devices, instruments and control requirements of 1150mm hot strip steel mill in a certain actual Iron & Steel Co., the laminar cooling control system is designed, including hardware figuration, network framework, software functions, mathematical model, etc. The engineering practice proves that the control system is steady and reliable, and it has the value being popularized in the other similar production line.

Development of Mathematical Model for Control Wear in Backup Roll for Hot Strip Mill

2014 ◽  
Vol 21 (1) ◽  
pp. 46-51 ◽  
Author(s):  
R. Servin-Castañeda ◽  
A. M. Garcia-Lara ◽  
R. D. Mercado-Solís ◽  
C. A. Vega-Lebrun
Keyword(s):  
Mathematical Model ◽  
Hot Strip Mill ◽  
Backup Roll ◽  
Hot Strip

Optimization of Model Adaption Based on Multi-Samples in Hot Strip Mill

2014 ◽  
Vol 543-547 ◽  
pp. 1233-1236
Author(s):  
Wen Peng ◽  
Geng Sheng Ma ◽  
He Nan Bu ◽  
Jian Zhao Cao ◽  
Dian Hua Zhang
Keyword(s):  
Control System ◽  
Production Process ◽  
Traditional Method ◽  
Single Sample ◽  
Hot Strip Mill ◽  
Hot Strip ◽  
Stable Production ◽  
Source Data ◽  
On Line ◽  
Length Direction

In order to improve the thickness precision, the model adaption method is of great concern which is a necessary component in the thickness control system. The sample concept is first taken into the model adaption in hot tandem mill, from which the learning coefficients are updated by a series of samples. Comparing to the single sample in traditional method, the new method can consider the variance in the length direction. And the source data is more comprehensive, the robustness is increased with flexible proportion coefficients. The thickness precision in stable production process is enhanced to 35μm. On-line result shows practical value and on-line application prospect.

An FE Based On-line Model for the Prediction of Work Roll Thermal Profile in Hot Strip Rolling

2010 ◽  
Author(s):  
Ji Won Choi ◽  
Jung Hyeung Lee ◽  
Cheng Gang Sun ◽  
Sang Moo Hwang ◽  
F. Barlat ◽  
...  
Keyword(s):  
Work Roll ◽  
Hot Strip Rolling ◽  
Strip Rolling ◽  
Thermal Profile ◽  
Line Model ◽  
Hot Strip ◽  
On Line

Development and Application of Advanced Coiling Temperature Control System in Hot Strip Mill

2011 ◽  
Vol 421 ◽  
pp. 140-146 ◽  
Author(s):  
Liang Gui Peng ◽  
En Yang Liu ◽  
Dian Hua Zhang ◽  
Xiang Hua Liu ◽  
Fang Xu
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Heat Radiation ◽  
Hot Strip Mill ◽  
Case Based Reasoning ◽  
Laminar Cooling ◽  
Coiling Temperature ◽  
Hot Strip ◽  
Tracking Model ◽  
Coiling Temperature Control

Run out table cooling equipment and coiling temperature control (CTC) system, especially mathematic models of a hot strip mill were introduced. Heat transfer models such as air convection model, heat radiation model and laminar cooling model, process control models such as segment tracking model, feedback control model, self-learning model and case-based reasoning model were detailed described. Since online application of the new CTC system, the laminar cooling control system has been running stably and reliably with a high precision of coiling temperature.

Recrystallisation Texture of Cold Rolled and Annealed IF Steel Produced from Ferritic Rolled Hot Strip

2004 ◽  
Vol 467-470 ◽  
pp. 257-262 ◽  
Author(s):  
A. Elsner ◽  
Radko Kaspar ◽  
Dirk Ponge ◽  
Dierk Raabe ◽  
Sybrand van der Zwaag
Keyword(s):  
Mechanical Properties ◽  
Rolling Texture ◽  
Salt Bath ◽  
Continuous Annealing ◽  
Coiling Temperature ◽  
Final Thickness ◽  
Hot Strip ◽  
Cold Rolled ◽  
Ferritic Rolling ◽  
Bath Furnace

The ferritic rolling strategy allows for the production of two different hot strip grades, a "soft" and a "hard" hot strip. The "soft" hot strip is rolled in the upper ferrite region and a sufficiently high coiling temperature ensures direct recrystallisation in the coil. The "hard" hot strip is rolled at relatively lower temperatures in the ferrite temperature region and exhibits a strained microstructure with a desirable rolling texture. Furthermore, these ferritic rolled hot strips can be used as initial strip for subsequent cold rolling. The current investigation focuses on the development of the recrystallisation texture of cold rolled and annealed ferritic rolled hot strip for different cold reductions. For this purpose "soft" and "hard" hot strips were produced on a laboratory hot rolling mill. These strips were cold rolled with a total reduction of 40 to 80% to a final thickness of 0.5mm. Subsequently the strips were subjected to simulated continuous annealing, using a salt bath furnace. The macro texture of both types of specimens was measured and correlated to the mechanical properties, including the Lankford values. A very different development of the recrystallisation texture and hence mechanical properties has been observed. However, both grades yielded improved deep-drawing properties.

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