应用RBF神经网络预测冷连轧机轧制力

张俊明;刘军;康永林;杨荃

钢铁 ›› 2007, Vol. 42 ›› Issue (8) : 46-0.

欢迎访问《钢铁》官方网站!今天是 2025年7月28日 星期一
钢铁 ›› 2007, Vol. 42 ›› Issue (8) : 46-0.
压力加工

应用RBF神经网络预测冷连轧机轧制力

  • 张俊明1,2,刘军2,康永林1,杨荃3
作者信息 +

Application of RBF Neural Networks to Prediction of Rolling Force of Tandem Cold Mill

  • 张俊明1,2,刘军2,康永林1,杨荃3
Author information +
文章历史 +

摘要

针对传统轧制力模型的固有缺陷,为提高冷连轧机组轧制力预测精度,使用一种RBF算法的人工神经网络预测冷轧带钢屈服应力,把预测值用于传统数学模型中计算轧制力;并在此基础上,组合使用机架相关网络(RBF类型)、速度相关网络(RBF类型)修正轧制力计算值。应用结果表明,此方法满足生产的需要,预报最终误差范围为±6.5%。

Abstract

In view of intrinsic imperfection of traditional models of rolling force, in order to improve the prediction precision of rolling force of tandem cold mill, a sort of artificial neural networks with RBF algorithm was used to predict yield stress of cold rolled steel strip,and then this value was used to calculate rolling force with traditional mathematical model; and then the stand network(RBF type), speed network(RBF type) were combined to correct calculated rolling force. Application of this method indicated that it has a final error within ±6.5%.

关键词

RBF算法 / 人工神经网络 / 轧制力预测 / 冷连轧机

Key words

RBF algorithm / artificial neural networks / prediction of rolling force / tandem cold mill

图表

引用本文

导出引用
张俊明, 刘军, 康永林, . 应用RBF神经网络预测冷连轧机轧制力[J]. 钢铁, 2007, 42(8): 46-0
ZHANG Junming, LIU Jun, KANG Yonglin, et al. Application of RBF Neural Networks to Prediction of Rolling Force of Tandem Cold Mill[J]. Iron and Steel, 2007, 42(8): 46-0

Accesses

Citation

Detail

段落导航
相关文章

/