An Improved Model for Camber Generation during Rough Rolling Process

Kang, Young-Nam; Jang, Yu Jin; Choi, Yongjun; Lee, Dukman; Won, Sangchul

doi:10.2355/isijinternational.isijint-2015-088

Cited by 13 publications

(5 citation statements)

References 5 publications

(5 reference statements)

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“…Jiong et al 11) constructed a three-dimensional simulator for the rough rolling process using FEM, in this work, an output feedback fuzzy controller that does not require a mathematical model is then designed to reduce camber including the lateral bar movement called side-slipping by tilting the roll. Kang et al 12) proposed a new model for curvature of the centerline at the exit side and the model assumes that the curved strip is generated only by the difference between the velocities of the sides of the strip.…”

Section: Introductionmentioning

confidence: 99%

Camber Prediction Based on Fusion Method with Mechanism Model and Machine Learning in Plate Rolling

Ding

Kong

et al. 2021

ISIJ Int.

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In order to realize the high-accuracy prediction of steel plate camber and the accurate control of roll gap tilt for straightness, a fusion method with mechanism model and machine learning of the strip at the exit side is investigated. Based on the basic equation of transverse asymmetric rolling, a mathematical model of plate camber curvature radius of the exit side and entry side is derived. Meanwhile, a machine vision method for camber measuring is adopted in which the subpixel coordinates of the rolled piece edges can be obtained, and the size of the plan view of rolled piece can also be settled indirectly to carry out feedback control on the camber defect. Tilt value of the roll gap can be controlled in advance to avoid the occurrence of camber which predicted with high accuracy. Prediction model of camber synthesis leveling based on PSO-LSSVM algorithm is used, the relative error is within ± 5% of both the training set and the testing set. Combine the mathematical model of roll gap tilt adjustment and PSO-LSSVM camber prediction, the roll tilt adjustment for different processes and product specification is calculated by predicting plate camber accurately to obtain good straightness for the final product, the relative error range of curvature value is within ± 6% after being compensated by PSO-LSSVM algorithm. The research result reveals that this method is suitable for camber prediction and model optimization in plate rolling process.

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Section: Introductionmentioning

confidence: 99%

Camber Prediction Based on Fusion Method with Mechanism Model and Machine Learning in Plate Rolling

Ding

Kong

et al. 2021

ISIJ Int.

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“…In order to determine the process parameters, predictive analytical modeling has been an important tool and has been considered thoroughly [5][6][7][8]. Several models that calculate the bending force's influence on the plates' shape have been suggested by many researchers.…”

Section: Introductionmentioning

confidence: 99%

“…Several models that calculate the bending force's influence on the plates' shape have been suggested by many researchers. Kang et al [8] provided a model that considers the dependence of the strips' curvature on the velocity difference of the sides of the strip. Nandan et al [4] identified both process parameters and pass schedule for optimum crown and flatness in hot rolling.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Plate Crown during Aluminum Hot Flat Rolling by Finite Element Modeling

Gavalas

Papaefthymiou

2019

JMMP

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The roll deflection during hot rolling can result in uneven thickness distribution across the width of a plate (crown). A conventional rolling mill is equipped with bending systems that can control this convex shape of the plate. However, the determination of the proper bending load is very complicated as the plate crown is influenced by the rolling conditions. In this paper, a thermo-mechanical Finite Element Model on LS-DYNA™ software was utilized to predict crown evolution based on the rolling conditions in order to determine the setting values for achieving the target crown. The simulation results were compared and verified with actual industrial data for rolling force, plate temperature and plate crown. This approach is essential for pass schedule design and process parameter optimization in order to achieve the desired product quality.

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“…Hot rolling in a rougher mill, which reduces the slabs and sends them to the finishing mill, is an essential step in the hot strip continuous rolling process. Owing to the different reductions on two sides of the hot rolling mill, the length of the rolled slab is also different on two sides, and consequently the slab camber is formed [1]. Slab camber is detrimental to the stability of subsequent finishing mill rolling process, and it may not only cause clogging of the finishing mill but also coiling defects such as strip edge folds and scrapes [2].…”

mentioning

confidence: 99%

Application of Takagi–Sugeno fuzzy model for slab camber control in a hot strip rougher mill

Yang

Wang

et al. 2020

Ironmaking & Steelmaking

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Control of slab camber is an important topic in hot strip rough rolling process. In this study, a slab camber control system, composed by a camber prediction model and a gap levelling value calculation model, based on the Takagi-Sugeno (T-S) fuzzy model is proposed. The performance of the developed camber prediction model is evaluated by the estimation error between the predicted and measured values of slab camber after rough rolling with the validation set from a rougher mill. The results show that the percentage of bars with estimation error within the tolerance of ±30 mm is 94.1%. Moreover, the proposed control model is finally applied in the 1580 mm hot rough rolling process. The control model can reliably provide the suggested adjustment of gap levelling, and the percentage of slabs, of which the adjustment error meets the requirement for camber quality assurance, is 95.85%.

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An Improved Model for Camber Generation during Rough Rolling Process

Cited by 13 publications

References 5 publications

Camber Prediction Based on Fusion Method with Mechanism Model and Machine Learning in Plate Rolling

Camber Prediction Based on Fusion Method with Mechanism Model and Machine Learning in Plate Rolling

Prediction of Plate Crown during Aluminum Hot Flat Rolling by Finite Element Modeling

Application of Takagi–Sugeno fuzzy model for slab camber control in a hot strip rougher mill

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