FET Prediction and Analysis with Data-Driven method for Non-steady Stage in Endless Rolling

doi:10.3901/JME.260183

Abstract

Abstract: As a critical process parameter in endless rolling production line, the control accuracy of finishing entry temperature(FET) directly impacts the stability of final rolling temperature and product dimensional performance metrics. To address the insufficient computational precision of the FET control(FETC) model during the non-steady-state phase of endless rolling at a domestic steel plant, a data-driven prediction method integrating mutual information feature selection and long short-term memory(LSTM) is proposed. First, mutual information entropy is employed to quantitatively analyze the nonlinear correlation degree between process variables and FET, enabling optimal feature variable selection. Subsequently, an LSTM prediction model with deep sequence feature extraction capability is constructed, and particle swarm optimization is adopted to optimize the model’s hyperparameters. Experimental validation demonstrates that the proposed model achieves superior predictive performance, with evaluation metrics MAE (1.89 ℃), RMSE (3.07 ℃), and R (0.989 3) significantly outperforming other comparative models in the study. Furthermore, shapley additive explanations(SHAP) interpretability analysis is applied to elucidate the interaction mechanisms of key process parameters on FET. The precision of temperature control in the non-steady-state phase of endless rolling is enhanced by the proposed method, and substantial engineering value is offered for stabilizing the performance of thin-gauge high-strength hot-rolled products.

Key words: finishing entry temperature, data-driven modeling, mutual Information, LSTM

CLC Number:

TG335

DONG Zishuo, GUO Wei, YAN Leming, ZHANG Min, YU Meng, LI Jixin. FET Prediction and Analysis with Data-Driven method for Non-steady Stage in Endless Rolling[J]. Journal of Mechanical Engineering, 2025, 62(6): 163-173.

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URL: http://www.cjmenet.com.cn/EN/10.3901/JME.260183

http://www.cjmenet.com.cn/EN/Y2025/V62/I6/163

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