Effect of strip profile of hot-rolled silicon steel on transverse thickness difference of cold-rolled strip

Ma, Xiaobao; Bao, Ming; Li, Jiangjiang; Chen, Peng; Yong-heng, Peng; Ren, Zhongkai

doi:10.1080/03019233.2023.2166264

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…Flatness denoted as I is the relative extension difference between the center ribbon and edge ribbon, and the unit is IU. The expressions have been derived according to literature [26], and are shown in Equation (1) and Equation (2). L(y) and l(y) denote the length of the ribbon at the entry and at the exit of stand, respectively.…”

Section: Flatness Calculation Modelmentioning

confidence: 99%

“…Flatness is the overall expression of the longitudinal extension in the width range of the rolled strip cross section. Crown beyond an allowable range and poor flatness reduce the product value and adversely affect subsequent processing [1]. Flatness defects that may occur between the two stands have a detrimental effect on the stability of rolling and may even cause serious accidents such as breaking and piling-up of the steel strip during hot tandem rolling [2,3].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Study on Metal Transverse Flow Law and Model of Rolled Strip under Variable Specification in Hot Rolling

Chai,

Li,

Shang

2023

Metals

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The research on metal transverse flow under variable specification is of great significance for shape calculation and control in hot strip rolling. The finite element software ABAQUS 2016 is used to establish the elastic–plastic deformation model of a hot rolled strip to study the metal transverse flow. The edge transverse strain εe and center transverse strain εc are introduced to characterize metal transverse flow and calculate the strip flatness. The effect on εe, εc and the flatness increment of similarity of profile under different widths, thicknesses and reduction rates is simulated and calculated. The results show that the change in similarity of profile has a linear influence on εe and εc. The strip has the ability of flatness self-correction due to the metal transverse flow. The ksc of the strip with B = 700 mm is 0.87, which is significantly greater than the 0.45 ksc value of the strip with B = 2100 mm. Priority can be given to ensure the crown requirements during narrow strip rolling. The ksc of the strip with H = 50 mm is 0.45, which is higher than the 0.22 ksc value of the strip with H = 6 mm, and the ksc of the strip with ε = 50% is 0.52, which is higher than 0.30 ksc value of the strip with ε = 10%. It is more reasonable to adjust the crown to a greater extent in the upstream stand to meet the requirement of both flatness and crown for the large entry thickness reduction rate and self-correction ability. A metal transverse flow prediction model based on the full test simulation results is established, which can meet the requirement of crown setting at the exit of each stand and the rapid calculation of online flatness control, and can further make the crown and flatness reach the target values at the finishing exit.

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Section: Flatness Calculation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical Study on Metal Transverse Flow Law and Model of Rolled Strip under Variable Specification in Hot Rolling

Chai,

Li,

Shang

2023

Metals

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“…Povorov and Semenov tried to build a mathematical model for predicting material shape in profile rolling. [1] Analyzing the effect of the profile of the hot-rolled sheet on cold-rolling, Ma et al developed the ANN model [2].…”

Section: Introductionmentioning

confidence: 99%

Sectional Dimensions Identification of Metal Profile by Image Processing

Orak,

Şeker

2023

JCC

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In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the system parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The results obtained with small deviations from the real values showed that this method can be applied in a real-time production line.

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Wear prediction model of hot rolling backup roll based on FEM + ML algorithm

Lu,

Hao,

Wang

et al. 2024

Int J Adv Manuf Technol

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The wear of backup rolls will have a great impact on the quality of hot rolled strip sheet shape. In order to overcome the limitations of the finite element method (FEM) in calculating the wear of backup rolls in terms of efficiency and accuracy, this paper proposes a FEM+ML tandem hybrid model to optimise the prediction effect of the finite element method (FEM) on the wear of backup rolls. Firstly, a backup roller wear model is established based on FEM. Secondly, in order to select the optimal machine learning (ML) algorithm as the finite element error compensation model, three types of finite element error compensation models were established based on the random forest (RF) algorithm, radial basis neural network (RBF) algorithm, and particle swarm optimisation support vector machine (PSO-SVM) algorithm. Finally, the three types of finite element error compensation models were connected in series with the FEM model to compare the prediction performance of the three types of FEM+ML models on the wear of backup rolls. The numerical experimental results show that the FEM+PSO-SVM model can predict the wear of the backup roll better, and the PSO-SVM algorithm is most suitable for establishing the finite element error compensation model. It is proved that the FEM+ML model proposed in this paper can effectively improve the accuracy and computational efficiency of the FEM model for predicting the wear of the backup rolls without adding microelements. In addition, among the hot rolling parameters, the rolling force has the greatest influence on the wear of the backup rolls, and excessive rolling force should be avoided for a single pass in order to slow down the wear of the backup rolls.

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Effect of strip profile of hot-rolled silicon steel on transverse thickness difference of cold-rolled strip

Cited by 4 publications

References 27 publications

Numerical Study on Metal Transverse Flow Law and Model of Rolled Strip under Variable Specification in Hot Rolling

Numerical Study on Metal Transverse Flow Law and Model of Rolled Strip under Variable Specification in Hot Rolling

Sectional Dimensions Identification of Metal Profile by Image Processing

Wear prediction model of hot rolling backup roll based on FEM + ML algorithm

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