• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1597-1603
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• 1995

A prediction model on forward slip has been developed for presetting rolling speed of each finish mill stand in the continuous hot strip roduction. Those factors such as neutral point, friction coefficient, volume fractions undergoing width spread, shape of deformation zone at each side of entry and delivery of the rolls were taken into account. To reduce the speed unbalance between adjacent stands a refining method of adjusting friction coefficient has also been developed. On-line application of the model showed a good agreement in rolling speeds between the predictions and the actual measurements, and gave an outstanding improvement in the travelling stability of strip passing through the finishing mill train.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.169-169
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• 2000

The modeling for the looper of a hot strip finishing mill to control the tension of the strip is presented. The looper is an arm pushing against the strip between stands in a tandem mill to keep the strip tension constant and to isolate the interactions of the adjacent stands. Tension is influenced by the difference in mass flow through the up stream and down-stream rolling stands. Tension is critical to strip quality, influencing width, gauge, and shape. This paper presents how looper angle and strip tension are controlled for a hot strip finishing mill.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.374-374
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• 2000

In this paper, we developed an ANFIS controller through ES algorithm for disturbances rejection in Hot Rolling. The looper of a Hot Rolling is installed between each pair of stands and plays key roles to enhance the product quality of the strip by controlling the tension and the width of the strip. At the same time, the AGC on top of the Mill produces a strip with the desired thickness through pressing its Mill. Between both, however, interactions are caused by coupling effects among strip tension, looper angle and strip thickness. In addition, in case disturbances, it is more difficult to keep strip quantities desirable. So we present an ANFIS controller through ES algorithm which is able to identify fuzzy rule with input/output data and update itself through output errors.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.819-827
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• 1992

Investigations of the fatigue damage of roughing mill roll and experimentally. By the computer simulation for analysing the stresses on the roll surface and experimental hot rolling, the following results were drawn : The crakcs observed on the roll surface were initiated thermally in the initial stage of the rolling and propagated by repeated thermal and bending stresses. The size of the roll surface cracks smaller than 4.87mm could avoid the occurrence of tiny scab, surface defect of hot steel strip. Since the size of surface cracks observed on the roughing mill roll was very small, the fatigue damage of roll surface was found not to be the major factor for the formation of the scab.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.73.3-73
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• 2001

Finishing mill (FM) is set up with rolling conditions (rolling speed, rolling force, roll gap, etc.) calculated by a FSU (Finisher Setup) model considering the temperature, qualities and size of a transfer bar and a strip at the entry and exit of FM before the transfer bar is rolled through FM. If the accuracy of setup is low mass flow unbalance occurs, so that the accuracies of the strip thickness and width become lower or rolling operation fault occurs. Therefore, to enhance the performance of the FSU model and to improve mass flow and the thickness accuracy of a strip in the 7-stand finishing mill using a hot strip speed measurement system. This study is being performed. In this paper, the speed measurement system, a developed neural network for predicting ...

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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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.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.56-59
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• 1988

The main purpose of Set-up control of hot strip mill plant is to obtain the most regular thickness. Then the learning or adaptive computer control in hot strip rolling mill has been developed. But it is very difficult to keep the inter-stands load distribution ratio uniform; so that the deviation of strip flatness is not avoidable. This leads to the degradation of quality of the products. In this report, an improved method base on the steepest descent method including the computation of optimum step size. This method is applied to the off-line simulation. In consequence, the better balances of inter-stands load distribution is achieved in addition to improvements of output thickness of hot strip mill in POSCO.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.168.2-168.2
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• 2005