Transactions of Materials and Heat Treatment

Title：Prediction on horizontal force in cold continuous rolling based on hybrid artificial neural network

Authors： Xia Junyong1 Lu Qi1 Zhang Zijian2 Zhou Hongdi1

Unit： 1.Hubei University of Technology 2.WISDRI Engineering & Research Incorporation Limited

KeyWords： cold continuous rolling mill strip steel rolling working roll hybrid artificial neural network particle swarm optimization algorithm

ClassificationCode：TG335.56

year,vol(issue):pagenumber：2024,49(3):86-93

Abstract：

For the problem that it is difficult to use the traditional mathematical model to calculate the horizontal force of working roll along the direction of strip steel movement in the cold continuous rolling mill roll system, a hybrid artificial neural network model was proposed to predict it, and the stress situation of working roll during the rolling process was analyzed. Then, based on the monitored state parameters, several types of parameters that had an impact on the horizontal force acting on the working roll along the direction of strip steel movement, such as rolling force, bending moment, tension, strip steel thickness and bending force, were selected as input variables, and two new particle swarm optimization algorithms were proposed to optimize the initialization weights and thresholds of artificial neural networks.The prediction analysis results show that the proposed improved hybrid artificial neural network can improve the prediction accuracy of the model compared with that before improvement, and the fitting accuracy is more than 90%, which can be used to guide the actual production.

Funds：

国家自然科学基金资助项目（52005168）；武汉市科技成果转化专项（2020030603012342）；湖北省科技创新人才计划（2023DJCO68）

作者简介：夏军勇（1976-），男，博士，教授，E-mail：20171013@hbut.edu.cn；通信作者：卢奇（1995-），男，硕士研究生，E-mail：dzyx671@126.com

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