Flatness Analysis and Control of Strips with Different Thickness in 2250 mm Hot Tandem Rolling

Chai, Xiaojun; Li, Hongbo; Zhang, Jie; Zhou, Yizhong; Ma, Heng-Hao; Zhang, Pengwu

doi:10.1002/srin.201800404

Cited by 11 publications

(6 citation statements)

References 23 publications

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“…Pesin and Pustovoytov [23] found that the mechanism of crack movement during plate rolling was the slab front and rear surface tilt caused by the temperature gradient of upper and lower surfaces. Chai et al [24] used the flatness calculation model to analyse and compare the flatness and longitudinal residual stress evolution during the rolling process of thick plate and thin plate. Aridi et al [25] drew the temperature field after the last pass through mathematical modelling and on-site temperature measurement, and they found the cooling curve under various operating conditions.…”

Section: State Of the Artmentioning

confidence: 99%

Shape Change Simulation Analysis of Wheel Steel in a Four-High Hot Rolling Mill

Liu¹,

Cui²,

Li³

et al. 2022

Int. j. simul. model.

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To reveal the shape change characteristics during the rolling process of the four-high hot continuous rolling mill, a three-dimensional finite element model was built with the wheel steel 380CL as the sample. The equivalent stress field, strain field, and displacement change of thickness of the wheel steel in each rolling process were analysed, and the field measurement and verification analysis were carried out. Results show that the equivalent stress, strain and thickness displacement of the strip edge gradually increases with the rolling, respectively. Reasonable tension before and after loading can effectively reduce the equivalent stress in the deformation zone and the rolling pressure required during rolling. The difference between the simulated rolling outlet thickness of 7.61 mm and the field measured thickness of 7.69 mm is small, which verifies that the calculation accuracy of the finite element is high. The conclusions obtained in this study provide a basis and reference for the development of similar wheel steel rolling calculation model.

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Section: State Of the Artmentioning

confidence: 99%

Shape Change Simulation Analysis of Wheel Steel in a Four-High Hot Rolling Mill

Liu¹,

Cui²,

Li³

et al. 2022

Int. j. simul. model.

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show abstract

“…As both P and M are in the 3D feature space, the FAE matrix of the two points, namely, Eff P and Eff M , can be obtained by the optimization model described in Section 3.2. 4) The FAE of actual operating point O can be calculated by FAE of insinuation (mapping) point M and projection point P. The calculation method is shown in Equation (16).…”

Section: Prediction Model Of Faementioning

confidence: 99%

“…As FAE can quantify the influence of each flatness actuator on the flatness of strip, most of current flatness control systems have been developed based on it. [13][14][15][16] As shown in Figure 2, a typical automatic flatness control system is usually composed of closed-loop control and feed-forward control, both of which are developed based on FAE.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Prediction Model of Flatness Actuator Efficiency in Cold Rolling Process Based on Process Data

Wang

Jin

et al. 2021

steel research int.

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The accuracy of flatness actuator efficiency (FAE) is a prerequisite to achieve high precision automatic flatness control. This study proposes an accurate acquisition approach of FAE based on the combination of simulation modeling and data‐driven modeling for flatness control of cold‐rolled strip. First, a 3D rolling feature space model is constructed according to the change interval of rolling process parameters based on rolling conditions. A 3D finite element simulation model is subsequently established to determine the prior value of actuator efficiency at each node in the feature space model. Then, to improve the accuracy of prior value, an online optimization model is developed by means of data‐driven mechanism. The sorting algorithm and the central limit theorem are introduced to filter the measured process data and calculate the variable weighting. The processed data are imported into the model to improve the fitting model. Finally, a linear output prediction model based on the trend extrapolation method is proposed to realize the accurate acquisition of FAE under any rolling conditions. The data analysis of the production process shows that the model is adaptive and accurate, which can realize high precision flatness control.

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“…[5][6][7] For the hot rolling of strip, the flatness problem will come out when the internal residual stress exceeds the critical value. [8][9][10][11] The determination of the critical stress depends on the buckling model. [12][13][14][15][16][17] Due to the high-temperature phase transformation characteristics of some steel grades, like thin gauge and high strength steel or non-oriented electrical steel, 18) the multiphase rolling caused by uneven temperature distribution along the strip width is inevitable during hot finishing rolling as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Effect of Uneven Distribution of Material Property on Buckling Behavior of Strip during Hot Finishing Rolling

Liu

et al. 2023

ISIJ Int.

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Unlike traditional austenitic rolling, there is phase transformation during hot finishing rolling for thin gauge and high strength steel or non-oriented electrical steel. The transverse differences of temperature and asynchronous phase transformation result in uneven distribution of material property of rolled strip, further change the buckling behavior of strip during hot finishing rolling. By replacing the elastic modulus constant in the traditional buckling model with the distribution function of tangent modulus obtained by multiphase compression experiments and multifield coupling simulation, the effect of uneven distribution of material property on the critical buckling stress and buckling wave length are analyzed. The results show that for the global longitudinal wave, the critical buckling stress at the exit of stand is greater than that at the entry. But the opposite is true for the local longitudinal wave. Under the effect of uneven distribution of material property, the critical buckling stress and buckling wavelength of global and local center waves change little. The critical buckling stress of global edge wave is almost unchanged, but the buckling wavelength decreases slightly. The critical buckling stress and buckling wavelength of local edge wave are reduced obviously, and the buckling wavelength is decreased by about 10%. It means that the existence of soft ferrite at the strip edge easily makes the wave mode develop to "fragmented edge wave", which is consistent with the actual phenomenon.

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Flatness Analysis and Control of Strips with Different Thickness in 2250 mm Hot Tandem Rolling

Cited by 11 publications

References 23 publications

Shape Change Simulation Analysis of Wheel Steel in a Four-High Hot Rolling Mill

Shape Change Simulation Analysis of Wheel Steel in a Four-High Hot Rolling Mill

Optimization and Prediction Model of Flatness Actuator Efficiency in Cold Rolling Process Based on Process Data

Effect of Uneven Distribution of Material Property on Buckling Behavior of Strip during Hot Finishing Rolling

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