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Whole process prediction model of silicon steel strip on transverse thickness difference based on Takagi-Sugeno fuzzy network

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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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Acknowledgements

This work was financially supported by the National Key Research and Development Plan of China (No. 2020YFB1713600), the National Natural Science Foundation of China (No. 51975043), the Fundamental Research Funds for the Central Universities (Nos. FRF-TP-19-002A3 and FRF-TP-20-105A1), and the China Postdoctoral Science Foundation (No. 2021M690352).

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Authors and Affiliations

  1. National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing, 100083, China

    Hai-nan He, Zhuo-hao Dai, Xiao-chen Wang, Quan Yang, Jian Shao & Jing-dong Li

  2. Handan Iron and Steel Company of Hebei Iron and Steel Group Co., Ltd., Handan, 056015, Hebei, China

    Zhi-hong Zhang & Liang Zhang

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  1. Hai-nan He
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  2. Zhuo-hao Dai
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  4. Quan Yang
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  5. Jian Shao
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  7. Zhi-hong Zhang
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Correspondence to Hai-nan He.

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Conflict of interest

Xiao-chen Wang and Jian Shao are youth editorial board members for Journal of Iron and Steel Research International and were not involved in the editorial review or the decision to publish this article. The authors declare that there is no conflict of interest.

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He, Hn., Dai, Zh., Wang, Xc. et al. Whole process prediction model of silicon steel strip on transverse thickness difference based on Takagi-Sugeno fuzzy network. J. Iron Steel Res. Int. 30, 2448–2458 (2023). https://doi.org/10.1007/s42243-023-01094-1

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  • DOI: https://doi.org/10.1007/s42243-023-01094-1

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