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A novel intelligent method for slab front-end bending control in hot rolling

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Abstract

A novel intelligent control strategy based on machine learning (ML) and an optimal feed-forward control method are proposed to realize the high-precision prediction and precise control of slab front-end bending in hot rolling. By analyzing the mechanism of slab front-end bending, the factors influencing hot rolling slab front-end bending are analyzed by a simulation model, and the actuator efficiency model of slab front-end bending is established. Through exploring the genetic law of slab front-end bending, an optimization design for slab front-end bending control that combines bar feed-forward with pass feed-forward is presented. By comparing different ML methods, the XGBoost model is selected to establish a prediction model and is combined the proposed optimal control strategy to realize slab front-end bending control. The proposed control strategy has been successfully applied to industrial sites and achieved satisfactory results, which the proportion of the serious slab turn-up phenomenon has been reduced by 11.12%, and the proportion of bending values within 50 mm has increased by 18.56%. The product quality is significantly improved, and automatic control of slab front-end bending for hot rolling is realized.

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Funding

This work is financially supported by the National Key Research and Development Plan (Grant No. 2020YFB1713600); the National Natural Science Foundation of China (Grant No. 51975043); and the Fundamental Research Funds for the Central Universities (Grant No. FRF-TP-20-105A1).

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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

    Lebao Song, Dong Xu, Hainan He, Xiaochen Wang & Quan Yang

  2. SAIC-GM-Wuling Automobile Co., Ltd, Liuzhou, 545000, Guangxi, China

    Chengyun Wang

  3. 2250 Hot Strip Mill, Hunan Lianyuan Iron and Steel Co., Ltd, Loudi, 417000, Hunan, China

    Hui Li & Haijun Yu

Authors
  1. Lebao Song
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  2. Dong Xu
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  3. Chengyun Wang
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  4. Hainan He
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  5. Xiaochen Wang
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  6. Hui Li
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  7. Haijun Yu
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  8. Quan Yang
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Contributions

Lebao Song: Writing, original draft; software. Dong Xu: Conceptualization, data validation. Chengyun Wang: Methodology. Hainan He: Software, visualization. Xiaochen Wang: Writing—review and editing. Hui Li: Resources, investigation. Haijun Yu: Investigation, data validation. Quan Yang: Supervision.

Corresponding author

Correspondence to Dong Xu.

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Song, L., Xu, D., Wang, C. et al. A novel intelligent method for slab front-end bending control in hot rolling. Int J Adv Manuf Technol 126, 4199–4212 (2023). https://doi.org/10.1007/s00170-023-11367-4

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