• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 제5회 압연심포지엄 신 시장 개척을 위한 압연기술
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• pp.349-358
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• 2004

The strip temperature history of finishing mill process is one of the most important factors to stabilize the facilities and to achieve the better product quality including a better prediction of roll force etc. The ultimate goal of this study is to improve scientific understanding of the finishing mill process in the view of heat transfer science. Finishing mill cooling facilities of KwangYang $\#3$ hot rolling are introduced and heat transfer analyses from FET to FDT are particularly focused in this study Three major tasks are successfully achieved as follows: 1) The temperature Prediction Models are developed. 2) The average absolute error is found to be less then 10 Celsius degree (about $8.5^{\circ}C$). 3) Prediction rate (less then $\bar{+}20$) are $10.2\%$ improved $(80.1\;\rightarrow\;90.3\%)$.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.212-212
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• 2000

This study was performed to construct a hot strip speed measuring system and check over whether the measured speed can be used for improving the mass flow of the head-end part of a hot strip in the 7-stand finishing mill. Because the mass flow in hot rolling mill affects the looper operation and the thickness and width control of a strip, accurate measurement of strip speed ie important. The measured speed was compared with the roll speeds of No. 6 and No.7 stand to check the performance of the system and analyzed to find how to apply the speed. As a result, it is shown that the accuracy of the system is enough, strip thickness error can be reduced by -275∼+200$\mu\textrm{m}$ using the measured speed and the existing FSU model has low accuracy for predicting forward slip rate. A neural network was developed to calculate forward slip rate instead of FSU model. The test result of the neural network shows that the neural network is more accurate than the FSU model.

• 제어로봇시스템학회논문지
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• 제14권3호
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• pp.295-300
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• 2008

In this paper, a new looper controller is proposed to minimize the tension variation of a strip in the hot strip finishing mill. The proposed control technology is based on a receding horizon control (RHC) to satisfy the constraints on the control input/state variables. The finite terminal weighting matrix is used instead of the terminal equality constraint. The closed loop stability of the RHC for the looper system is analyzed to guarantee the monotonicity of the optimal cost. Furthermore, the RHC is combined with a 4SID(Subspace-based State Space System Identification) model identifier to improve the robustness for the parameter variation and the disturbance of an actuator. As a result, it is shown through a computer simulation that the proposed control scheme satisfies the given constraints on the control inputs and states: roll speed, looper current, unit tension, and looper angle. The control scheme also diminishes the tension variation for the parameter variation and the disturbance as well.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 제7회 압연 심포지엄
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• pp.97-102
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• 2009

In hot strip rolling, sound prediction of the temperature of the strip is vital for achieving the desired finishing mill draft temperature (FDT). In this paper, a precision on-line model for the prediction of temperature distributions along the thickness of the strip in the finishing mill is presented. The model consists of an analytic model for the prediction of temperature distributions in the inter-stand zone, and a semi-analytic model for the prediction of temperature distributions in the bite zone in which thermal boundary conditions as well as heat generation due to deformation are predicted by finite element-based, approximate models. The prediction accuracy of the proposed model is examined through comparison with predictions from a finite element process model.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 춘계학술대회논문집
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• pp.176-179
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• 2003

The mean temperature prediction of strip is very important in hot strip finishing mill because of affecting on product quality and shape. Also, temperature can be used by basic information in other on-line control models with affecting control accuracy in factory. So, FE based on-line temperature model was developed for predicting strip mean temperature accurately in various process conditions and factory environments. There are many variables in affecting strip mean temperature in on-line states of factory. But some problems are occurred in considering all variables for making temperature model because of the bad efficiency of regression or fitting analysis. In this report, we have adopted dimensional analysis for solving these problems. We have many variables with dimensions affecting strip temperature but we are able to make non-dimensional variables less than dimensional variables from the combination of dimensional variables caused by PI-Theorem in fluid mechanics. The developed models are divided by two parts. The one is interstand temperature prediction model. The other is roll gap temperature model.

• 조명전기설비학회논문지
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• 제27권6호
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• pp.59-67
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• 2013

This paper presents a neural net type process model for enhancing learning compensation function in hot strip finishing rolling mill. Adequate input and output variables of process model are chosen, the proposed model was designed as single layer neural net. Equivalent carbon content, strip thickness and rolling speed are suggested as input variables, and looper's manipulation variable is proposed as output variable. According to simulation result using process data to show the validity of the proposed process model, neural net type process model's outputs give almost similar data to process output under same input conditions.

• Journal of Mechanical Science and Technology
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• 제18권3호
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.

• 소성∙가공
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• 제8권6호
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• pp.583-590
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• 1999

New forward slip model has been developed for the precise prediction of rolling speed in the hot strip finishing mill. Besides those influential factors such as neutral point, work roll diameter, friction coefficient, bite angle and the thickness at each side of entry and delivery of the rolls, roll torque was specifically taken into account in this study. To consider the effect of width change 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.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1996년도 춘계학술대회논문
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• pp.101-109
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• 1996

Mini-mill process which is one of the new steel -marking technologies to be able to produce the hot rolled coils by thin slab caster of ISP(In-Line Strip Production) type, will be completed in the Kwangyang Steel Works of POSCO in August, 1996, SEt-Up Model of finishing mill which consists of 5 stands is the most basic and essential in mini-mill plant. Therefore, the simulation program of Finishing-mill Set-Up model were developed in this research , using new temeprature prediction model, roll gap model and rolling physical model. Using the developed FSU program , pass schedules to produce the strips with target strip thickness of 1.8mm, 2.0mm, 2.3mm, 2.7mm an d3.0mm were also determined respectively.

• 대한기계학회논문집A
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• 제41권1호
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• pp.63-68
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• 2017

이 논문에서는 열간 사상압연 공정에서 스트립 통판성의 안정성과 판 품질 향상을 위하여 새로운 선진율 학습모델 개발에 관한 연구를 수행한다. 먼저 기존의 선진율 해석모델에 대한 고찰을 통해 스트립 장력, 루퍼 각도 그리고 롤 주속이 선진율 학습에 크게 영향을 미치는 주요 압연 인자들임을 보인다. 두 번째로는 선진율 학습의 주요 압연 인자들을 이용하여 새로운 선진율 학습모델을 도출한 후, 보조변수 규명 알고리즘을 이용하여 이산시간계 학습모델을 규명한다. 끝으로 컴퓨터 시뮬레이션을 통해 이 논문에서 제안한 새로운 학습모델이 기존의 학습모델보다 유용함을 보인다.