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| Whole process prediction model of silicon steel strip on transverse thickness difference based on Takagi-Sugeno fuzzy network |
| Hai-nan He1, Zhuo-hao Dai1, Xiao-chen Wang1, Quan Yang1, Jian Shao1, Jing-dong Li1, Zhi-hong Zhang2, Liang Zhang2 |
| 1 National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083, China 2 Handan Iron and Steel Company of Hebei Iron and Steel Group Co., Ltd., Handan 056015, Hebei, China |
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Abstract The hot rolling and cold rolling control models of silicon steel strip were examined. Shape control of silicon steel strip of hot rolling was a theoretical analysis model, and the shape control of cold rolling was a data-based prediction model. The mathematical model of the hot-rolled silicon steel section, including the crown genetic model, inter-stand crown recovery model, and hot-rolled strip section prediction model, is used to control the shape of hot-rolled strip. The cold rolling shape control is mainly based on Takagi-Sugeno fuzzy network, which is used to simulate and predict the transverse thickness difference of cold-rolled silicon steel strip. Finally, a predictive model for the transverse thickness difference of silicon steel strips is developed to provide a new quality control method of transverse thickness of combined hot and cold rolling to improve the strip profile quality and increase economic efficiency. The qualified rate of the non-oriented silicon steel strip is finally obtained by applying this model, and it has been steadily upgraded to meet the needs of product quality and flexible production.
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| Cite this article: |
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Hai-nan He,Zhuo-hao Dai,Xiao-chen Wang, et al. Whole process prediction model of silicon steel strip on transverse thickness difference based on Takagi-Sugeno fuzzy network[J]. Journal of Iron and Steel Research International, 2023, 30(12): 2448-2458.
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2023, Vol. 30 
