• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.723-727
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• 2003

In this paper, two methods are discussed for good rolling force prediction in a plate mill. One is about the development of a long and a short learning scheme using a Neural Network for normal rolling and the other is about a mathematical model improvement by considering microstructural changes for controlled rolling. The research results are implemented in a on-line system of Pohang Works in POSCO and the field tests have showed that the prediction accuracies of rolling force are highly improved.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.7
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• pp.1030-1041
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• 1997

The control model in the tandem cold rolling mill consists of many mathematical theories and is used to calculate the reference values such as the roll gap and the rolling speed for good operation of rolling mill. But, the control model used presently has a problem causing inaccurate prediction of the rolling force. By the parameter identification, it was found that the main factor causing inaccurate prediction of the rolling force was incorrect modeling of the friction coefficient and the flow stress. To get rid of the erroneous factor new adaptive schemes are suggested in this work. Those are a long-time adaptation by the iterative least-square method and a short-time adaptation by the recursive weighted least-square method respectively. The new equations for the friction coefficient and the flow stress are derived by applying the suggested adaptive algorithms. Through the on-line test in an actual mill, it is proved that the rolling force predicted by the new equations is more accurate than the one by the existing equations ever used.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.393-397
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• 2005

Since the braking system of rolling stock is directly linked to it's safety, ensuring reliability of braking system and evaluation of performance of it are very important. To develope the performance of braking system, it is required advanced technology and gradually various factors in the field test result. This study is designed to analyze the air pressure control about braking force in rolling stock, also, by comparing braking force of high speed railway with that of high speed train. This paper suggests to establish a method of computation of braking force form the air pressure control. And The high speed train researches into patterns of braking system such as the train of speed up and introduction of electric and pneumatic braking system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.323-323
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• 2000

In the tandem cold wiling mill, the quality is very in portant, and requirements for thickness accuracy become more strict. However, the mathematical model for prediction of rolling force was not considered an elastic deformation at the entry and delivery side of the contacted area between the worked roll and rolling strip so that there was so difficult to control of the thickness. To overcome this problem, the mathematical model included an elastic deformation of strip has been developed and applied to the field in order to predict the rolling force. The simulated results showed that the end of elastic recovery should be included the model, even if the effect of elastic compression was not important.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.368-373
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• 2003

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analysis the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks - RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.5
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• pp.96-103
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• 2001

The quality requirements for thickness accuracy in cold rolling continue to become more stringent, particularly in response to exacting design specification from automotive customers. One of the major impacts from the tighter tolerance level is more unusable product on the head end and tail end of tandem mill coils when the mill is in transition to or from steady state rolling condition. A strip thickness control system for a tandem cold steel rolling mills is composed with blocked non-interacting controller and controllers for strip thickness and tension control of each rolling stands. An intelligent mathematical model included an elastic deformation of strip has been developed and applied to the field in order to predict the rolling force. The simulated results showed that the effect of elastic recovery should be included the model, even if the effect of elastic compression was not important.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1296-1302
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• 2002

A mathematical model for cold rolling and temper rolling process of thin steel strip has been developed using the influence function method. By solving the equations describing roll gap phenomena in a unique procedure and considering more influence factors, the model offers significant improvements in accuracy, robustness and generality of the solution for the thin strip cold and temper rolling conditions. The relationship between the shape of the roll profile and the roll force is also discussed. Calculation results show that any change increasing the roll force may result in or enlarge the central flat region in the deformation zone. Applied to the temper rolling process, the model can well predict not only the rolling load but also the large forward slip. Therefore, the measured forward slip, together with the measured roll force, was used to calibrate the model. The model was installed in tile setup computer of a temper rolling mill to make parallel setup calculations. The calculation results show good agreement with the measured data and the validity and precision of the model are proven.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.6
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• pp.29-33
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• 2004

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analyze the performance of applied neural network the comparison with the measured rolling force and the predicted results using two different neural networks-RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• Journal of Welding and Joining
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• v.34 no.6
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• pp.20-27
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• 2016

This study deals with the proper conditions of the trail rolling method (TRM) for the prevention of the buckling welding distortion at the AA5083 GMA butt weldment. For it, the effect of the working conditions of TRM including the rolling depth and the rolling distance between the welding torch and the roller on the longitudinal welding shrinkage force of the weldment was evaluated by using 3 dimensional thermo-mechanical FE analyses. The longitudinal welding shrinkage force inducing the buckling welding distortion at the GMA butt weldment was mitigated with an increase in the rolling depth and the rolling distance between the welding torch and the roller. Based on the results, the proper conditions of trail rolling method were established to reduce the longitudinal welding shrinkage force of the GMA butt weldment to below the critical value corresponding to the bucking distortion.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.7
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• pp.275-286
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• 2001

The research presents an analytical theory to calculate the characteristics of the bal bearing with waviness in its rolling elements considering the centrifugal force and gyroscopic moment of bal. The effects of centrifugal force and gyroscopic moment are introduced to the kinematic constraints and force equilibrium equations. and the waviness of rolling elements is modeled by sinusoidal function to calculate the contact force at each ball. The numerical solutions of governing equation of berating due to waviness are calculated by using the Newton-Raphson method. The accuracy of the research is validated by comparing the contact force. contact angle in case of considering the centrifugal force and gyroscopic moment of bal and the contact force and vibration frequencies in cases of considering waviness with the prior researches respectively. It investigates the stiffness, contact force. displacement and vibration frequencies of the ball bearing considering not only the centrifugal force and gyroscopic moment of ball but also the waviness of the rolling elements.