锻压技术

基于GA-PELM的板材热连轧轧制力预测

英文标题：Rolling force prediction of hot strip rolling based on GA-PELM

作者：杨静任彦高晓文苏楠

分类号：TP183

出版年,卷(期):页码：2022,47(1):43-48

摘要：

在板材热连轧过程中，轧制力的计算精度直接影响板带钢的实际厚度，也是实现精准在线控制的前提。然而，由于实际的轧制过程受多种因素影响，使用传统模型进行预测的精度往往比较低。为了提高轧制力的预测精度，提出了并行异构极限学习机（PELM）的轧制力预测模型，该模型学习速度快且泛化能力强，同时为了保证模型的稳定性，采用遗传算法（GA）优化了该模型的权重和偏差。以包头某钢厂2250生产线的实际生产数据为例进行轧制力预测，结果表明，该算法训练的轧制力预测模型有很好的预测精度，适用于热连轧过程的轧制力预测。

In the process of hot strip rolling, the calculation accuracy of rolling force directly affects the actual thickness of strip steel, which is also the prerequisite of accurate online control. However, because the actual rolling process is affected by many factors, the prediction accuracy using the traditional model is often lower. Therefore, in order to improve the prediction accuracy of rolling force, the rolling force prediction model of parallel heterogeneous limit learning machine (PELM) was proposed, which had high learning speed and strong generalization ability, and at the same time, in order to ensure the stability of the model, the weight and deviation of the model was optimized by genetic algorithm (GA). Taking the actual production data of 2250 production line for a steel plant in Baotou as the example to predict the rolling force, the results show that the rolling force prediction model trained by the algorithm has good prediction accuracy and is suitable for the rolling force prediction of hot strip rolling process.

基金项目：

国家自然科学基金资助项目（62063027）；内蒙古自然基金资助项目（2019MS06002）；内蒙古自治区研究生教育创新计划

作者简介：杨静（1996-），女，硕士研究生 E-mail：15191734@qq.com 通信作者：任彦（1977-），女，博士，教授 E-mail：1121996049@qq.com

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