• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2003.05a
• /
• pp.176-179
• /
• 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.

• Transactions of Materials Processing
• /
• v.12 no.7
• /
• pp.668-674
• /
• 2003

Rigid-plastic finite element analyses on the deformation of slabs at various width reductions have been performed. By using commercial finite element code, dog-bone profile, crop profile and the longitudinal width profile after edging and Horizontal rolling have been analysed. The deformation behavior of slab for the heavy edger mill has also been compared with that for the sizing press. From the deformation analyses, it was found that the sizing press-horizontal rolling method is more efficient in width reduction than that of heavy edger mill-horizontal rolling. The results of finite element analyses fer the deformation of slab were well confirmed by the actual operational data. It was found that the amount of width variation after sizing and rolling is about 5∼10mm.

• Journal of Mechanical Science and Technology
• /
• v.18 no.3
• /
• pp.379-387
• /
• 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.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2009.04a
• /
• pp.97-102
• /
• 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.

• Transactions of Materials Processing
• /
• v.10 no.1
• /
• pp.53-58
• /
• 2001

Set-up reference values, used in determining the optimum downcoiling tension, we experimentally verified in this study. During the actual downcoiling, the strip suffers both tension and bending force through the rotation of mandrel. Therefore, simulative test which can measure both tension and bending resistance of strip was performed to estimate set-up reference value for strip tension during downcoiling operations. The values obtained from the simulative test were correlated with the yield stress which has conventionally been used as reference values for downcoiling tension. The correlative analysis showed that the yield stress of strip can be a good reference value for downcoiling tension. Furthermore, the bending load also shows strong correlation with simulated values due to the close relationship between yield stress and bending load.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.1
• /
• pp.63-68
• /
• 2017

This paper reviews the learning model of a forward slip ratio in order to improve the mass-flow stability and strip qualities in the hot strip finishing mill process. Firstly, it is shown, from mathematical analysis, that the significant parameters of the forward slip ratio are the tension, looper angle, and roll velocity. Secondly, a discrete-time learning model of the forward slip ratio is proposed from these parameters, which is identified by an instrumental variable (IV) identification algorithm. Finally, it is shown from computer simulation that the proposed learning model is more effective than the existing learning model.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.248-251
• /
• 1991

A robust monitor AGC(Automatic Gauge Control) system for a hot strip mill plant of POSCO Is designed by minimizing the H.inf. norm of a so called mixed sensitivity function. In order to solve the mininizatlon problem, a polynomial approach proposed by Kwakernaak[5] is used. The controller performance is tested by a computer simulation under various circumstances.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.53.4-53
• /
• 2001

This paper described about the system which can be inspect work roll surface for deciding a milling schedule and roll changing at hot strip mill in POSCO. Developed system consists of CCD camera, Xenon lamp with fiber bundle and mechanical control part. The water probe build up water pole between head of probe and roll surface to acquisite a good image from a work roll surface under the bad environment with steam, cooling water and high temperature. This system is possible to monitor a work roll surface of about 12${\times}$9mm. We have shown the validation of the developed system which can monitor the evolution of degradation on work roll surface.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2004.08a
• /
• pp.349-358
• /
• 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 $(80.1\;\rightarrow\;90.3\%)$.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.6
• /
• pp.59-67
• /
• 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.