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Predicting flatness of strip tandem cold rolling using a general regression neural network optimized by differential evolution algorithm

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Abstract

Flatness prediction is a critical technical concern in flatness feedforward control during strip cold rolling. This work realized a high-precision prediction of flatness for strip cold rolling by the data-driven and industrial Internet of Things (IIoT) technology and provided an effective mode for industrial data utilization. A flatness prediction model based on general regression neural network (GRNN) optimized by the differential evolutionary (DE) algorithm was proposed; an intact dataset was established by collecting data from the hot rolling and cold rolling production lines by develo** a cross-process IIoT platform, and the proposed model and other common data-driven models are trained and tested based on that. The experiment results obtained based on a dataset with 50,000 samples show that the proposed model is feasible and can achieve accurate prediction of flatness during the strip cold rolling, and compared with the BP and SVM model, it has a better performance.

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Funding

The work would like to thank the China Postdoctoral Science Foundation (Grant No. 2021M690352) for their financial support.

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Authors and Affiliations

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

    Jianwei Zhao, **gdong Li, Haotang Qie, **aochen Wang, Jian Shao & Quan Yang

  2. Institute of Engineering Technology, University of Science and Technology Bei**g, Bei**g, 100083, China

    Jianwei Zhao, **gdong Li, Haotang Qie, **aochen Wang, Jian Shao & Quan Yang

Authors
  1. Jianwei Zhao
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  2. **gdong Li
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  3. Haotang Qie
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  4. **aochen Wang
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  5. Jian Shao
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  6. Quan Yang
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Contributions

Jianwei Zhao: conceptualization; writing—review and editing; funding acquisition. **gdong Li: methodology; writing—original draft. Haotang Qie: resources, software. **aochen Wang: formal analysis, conceptualization. Jian Shao: formal analysis, methodology. Quan Yang: project administration, supervision.

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Correspondence to Jianwei Zhao.

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Zhao, J., Li, J., Qie, H. et al. Predicting flatness of strip tandem cold rolling using a general regression neural network optimized by differential evolution algorithm. Int J Adv Manuf Technol 126, 3219–3233 (2023). https://doi.org/10.1007/s00170-023-11330-3

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