• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.403-407
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• 2005

This paper proposes a looperless tension control algorithm which is robust to disturbance and tensional variation in rolling process using SVR(Support Vector Regression). Hot rolling process which is global technology to coil steel after continuous finishing process for welded bars followed by roughing mill process, becomes hot issue. Finishing mill process not only makes it possible to produce ultra thin steel strip(0.8 mm) but enhance the quality of terminals of coil, which increases the productivity due to faster process. Constant tension control between stands in hot rolling process is essential to enhance the quality of steel. Sensorless tension control is under research by some advanced companies to replace the conventional tension control method because in continuous finishing mill process, it is impossible to install the looper used in conventional control system. Simulation results show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.47-56
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• 1999

New rolling speed prediction model has been developed for the precise presetting rolling speed of each finishing mill stand in the tandem hot strip mill. Those factors such as neutral point, work roll diameter, rolling torque, friction coefficient, bite angle and the thickness at each side of entry and deliver of the rolls were taken into account. To consider width effect on forward slip, calibration factors obtained from rolling torque has been added to new prediction model and refining method has also been developed to reduce the speed unbalance between adjacent stands. The application of the new model showed a good agreement in rolling speeds between the predictions and the actual measurements, and the standard deviation of prediction error has also been significantly reduced.

• Transactions of Materials Processing
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• v.8 no.1
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• pp.65-77
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• 1999

In recent years, the quality requirements from the customers of hot rolled steel strip have been steadily increasing in diversity and strictness. To meet these quality requirements as well as to improve productivity, steel mills have been doing their efforts for developing high performance Automatic Gauge Control (AGC) system. However, it is very time consuming and also needs a lot of money to develop the new technologies of AGC in actual mill. So, there has been a demand for developing the Dynamic Hot Rolling Simulator since late 80's. It is a kind of software packages and can analyze the dynamic behaviors of hot finishing rolling process without laborious experiments in actual mill. It can also be used as a designing tool of Automatic Gauge Controller. In this work, the Dynamic Hot Rolling Simulator which is applicable to 6 sands hot strip mill rolling was developed. The MATLAB with SIMLINK was used as a software developer for making the main part of simulator because it is very powerful tool for modeling, integrating, controller design, and simulation. In this paper, the structures and the mathematical models of the simulator were briefly described and the results of simulation on the transient phenomena of hot rolling process with actual mill data were also presented.

• Transactions of Materials Processing
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• v.6 no.6
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• pp.482-488
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• 1997

New carbon equivalent equation for the better prediction for the better prediction of roll force in a continuous hot strip mill has been formulated by applying a neural network method. In predicting roll force of steel strip, carbon equivalent equation which normalize the effects of various alloying elements by a carbon equivalent content is very critical for the accurate prediction of roll force. To overcome the complex relationships between alloying elements and operational variables such as temperature, strain, strain rate and so forth, a neural network method which is effective for multi-variable analysis was adopted in the present work as a tool to determine a proper carbon equivalent equation. The application of newly formulated carbon equivalent equation has increased prediction accuracy of roll force significantly and the effectiveness of neural network method is well confirmed in this study.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2836-2844
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• 2000

Thickness control of hot-rolled strips has become an important issue in recent years because of the need for improving the quality of the hot-rolled strip. In this study, a modifying method of rolling force set-up with consideration of spread was developed to improve the thickness uniformity at the finishing rolling units in hot rolling. Through the analysis of real production data it was found that the accuracy of the rolling force determined from the finishing mill set-up (FSU) model dominantly governed the thickness uniformity in rolled plates at the front. Based on this analysis , several examples were selected to calculate the spread of rolled plate using three dimensional rigid thermo-viscoplastic finite element program. FE analysis results were used to train the neural network system that can predict the spread hot-rolled plate and the rolling force was modified based on the predicted value of spread. The modified rolling forces were closer to the measured rolling force so it can be expected that the accuracy of thickness uniformity of hot-rolled plate will be improved.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.336-345
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• 2004

Investigated via a series of finite-element(FE) process simulation is the effect of diverse process variables on some selected non-dimensional parameters characterizing the thermo-mechanical behavior of the roll and strip in hot strip rolling. Then, on the basis of these parameters, on-line models are derived for the precise prediction of the temperature changes occurring in the bite zones as well as in the inter-stand zones in a finishing mill. The prediction accuracy of the proposed models is examined through comparison with predictions from a FE process model.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.292-300
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• 1995

According to the number of cold-rolled coils, the amount of roll wear and thermal expansion, and roll gap profile were calculated, by using the actual data from the finishing mill. Also, based on those data, the calculations of the deflection, the flattening, and the contact pressure of vwork rolls and backup rolls were made respectively. Specially, in the calculation of contact pressure, the numerical results were obtained not only during the normal rolling, but also during the abnormal rolling, by modeling mathematically the dynamic impact force which occurs when the head section of the strip is threading through rolls. With those results the growth of the fatigue region and the fatigue damage of rolls were predicted. Also the optimum roll-grinding depth was determined to maximize the roll life.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.249-252
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• 1997

Mini-mill process which is one of the new steel making process to be able to produce the hot rolled strip by thin slab caster, was completed in the kwangyang steel work. The new process was constructed liquid core deduction, tandem reduction unit, induction heater, coil box and finishing mill to be varied width. Therefore, in oder to make sure of target strip width, analysis of actual plant data was done to fine out amount of width deviation. Finally, the predication system of width in the mini-mill process was developed to included temperature caculation model.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.175-183
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• 2004

In hot strip rolling, a capability for precisely predicting roll force is crucial for sound process control. In the past, on-line prediction models have been developed mostly on the basis of Orowan's theory and its variation. However, the range of process conditions in which desired prediction accuracy could be achieved was rather limited, mainly due to many simplifying assumptions inherent to Orowan's theory. As far as the prediction accuracy is concerned, a rigorously formulated finite element(FE) process model is perhaps the best choice. However, a FE process model in general requires a large CPU time, rendering itself inadequate for on-line purpose. In this report, we present a FE-based on-line prediction model applicable to precision process control in a finishing mill(FM). Described was an integrated FE process model capable of revealing the detailed aspects of the thermo-mechanical behavior of the roll-strip system. Using the FE process model, a series of process simulation was conducted to investigate the effect of diverse process variables on some selected non-dimensional parameters characterizing the thermo-mechanical behavior of the strip. Then, it was shown that an on-line model for the prediction of roll force could be derived on the basis of these parameters. The prediction accuracy of the proposed model was examined through comparison with measurements from the hot strip mill.

• Transactions of Materials Processing
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• v.6 no.2
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• pp.95-101
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• 1997

The thermal fatigue and wear properties of high speed steel roll which was recently developed were investigated by observing microstructure, by measuring mechanical and physical properties, by conducting thermal fatigue testing, and by measuring the amount of wear in actual mill. High speed steel roll had better thermal fatigue testing, and by measuring the amount of wear in actual mill. High speed steel roll had better thermal fatigue life than high chromium iron roll, which was due to lower carbide content, higher strength, and higher thermal conductivity. The amount of wear of high speed steel roll was nearly the same as that of high chromium iron roll in the first finishing stand, which was due to the oxide formation on the roll surface. However, in the third finishing stand, the wear resistance of high speed steel roll was 2~3 times as good as that of high chromium iron roll because the former had higher hardness at high temperature.