Development of FEM Simulator Combined with Camber Reducing Output Feedback Fuzzy Controller for Rough Rolling Process

Jeong, Daun; Kang, Young-Nam; Jang, Yu Jin; Lee, Dukman; Won, Sangchul

doi:10.2355/isijinternational.53.511

Cited by 12 publications

(6 citation statements)

References 22 publications

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“…[5][6][7][8][9] Shiraishi et al 10) introduced a modified exit-side curvature model that includes a camber change coefficient that should be tuned to account for various rolling conditions such as front and back tension. 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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“…Similarly, a serious strip camber also appeared on a 3000 mm mill of Handan Iron & Steel Corporation since 2012, and many influence factors, including wedge supplied strip, uneven temperature distribution of the strip, stiffness difference on both sides of the rolling mill, roll shape, EGC roll gap control etc., were analysed and finally the strip camber was improved to some degree by changing the installation position of the EGC sensor. A strip camber studied by Jeong et al 4 could be reduced by minimising the side-slipping and the bending from the rolling position to a certain distance. A new method, i.e.…”

Section: Introductionmentioning

confidence: 99%

Mechanism generating deviations in the rolling load and strip camber on the plate rolling mill

Shen

Ren

et al. 2016

Ironmaking & Steelmaking

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Both the support force inequality on both ends of the roll and the camber are common drawbacks, those were caused by the static indeterminacy of structure design, backlash and offset setting selection on the plate rolling mill. There are many technical literatures for analysing the reasons for generating of the strip camber, which are mainly the external factor analysis, however, the internal cause of the mill roll system is ignored. The negative effects of offset distance setting and side clearances of about 1 mm between the chocks and side surface of the housing window should be considered on the plate rolling mill. In reality, the primary cause of this deviation and the strip camber lies in the interaction between offset distance setting and cross of the rolls. The greater the offset setting value of the plate rolling mill, the greater the generation probability of pressure difference and the camber. Some measures, involving eliminating offset distance setting, effectively controlling the side clearances between chocks and housing window, eliminating initial cross and dynamic cross phenomenon, should be taken to maintain the rolls parallel and to prevent radically the support force inequality on both ends of the roll and strip camber.

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“…Therefore, it is easy to guess that the camber reducing scheme that can be applied in the first rolling pass is advantageous. Jeong et al 8) suggested a camber reducing scheme which can also be applied in the first rolling pass by adopting an output feedback fuzzy controller that uses simple empirical rules. In this study, a FEM simulation was combined with the fuzzy controller to verify the scheme's effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Camber Regulation in Rough Rolling Process Using Wedge Estimation of Incoming Bar

et al. 2015

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In this paper, a new algorithm to reduce camber based on an estimated entry-side wedge of the bar during rough rolling process is proposed. The entry-side wedge is estimated based on a simple mathematical model with the aids of the tangent vector variation and curvature, which can both be obtained using the measured bar centerline. The differential roll gap between drive-side and work-side was then adjusted to minimize the delivery-side curvature of the bar using this estimated entry-side wedge information. A three-dimensional simulator that describes a rough rolling process was constructed using FEM (Finite Element Method). The effectiveness of the proposed scheme was validated using FEM simulation combined with the proposed camber reducing algorithm.

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Development of FEM Simulator Combined with Camber Reducing Output Feedback Fuzzy Controller for Rough Rolling Process

Cited by 12 publications

References 22 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

Mechanism generating deviations in the rolling load and strip camber on the plate rolling mill

Camber Regulation in Rough Rolling Process Using Wedge Estimation of Incoming Bar

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