东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2005, Vol. 26 ›› Issue (8): 726-728.DOI: -

• 论著 • 上一篇    下一篇

基于神经网络的钢包精炼终点预报

高宪文;张傲岸;魏庆来   

  1. 东北大学教育部暨辽宁省流程工业综合自动化重点实验室;东北大学教育部暨辽宁省流程工业综合自动化重点实验室;东北大学教育部暨辽宁省流程工业综合自动化重点实验室 辽宁 沈阳 110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2005-08-15 发布日期:2013-06-24
  • 通讯作者: Gao, X.-W.
  • 作者简介:-
  • 基金资助:
    高等学校骨干教师资助计划项目．

Neural network based prediction of endpoint in ladle refining process

Gao, Xian-Wen (1); Zhang, Ao-An (1); Wei, Qing-Lai (1)   

  1. (1) Key Laboratory of Process Industry Automation, Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2005-08-15 Published:2013-06-24
  • Contact: Gao, X.-W.
  • About author:-
  • Supported by:
    -

RichHTML

1

PDF (PC)

977

摘要： 通过改进的BP神经网络,结合炼钢工艺的特点,建立炼钢精炼炉终点模型,对精炼炉终点进行预报,其基本思想是:在对以往的现场数据进行分析和了解及已有的人工神经元网络模型的基础上,结合炼钢的实际工艺特点,确定模型的参数,从而确定预报模型,再根据确定的模型对现场的其他数据进行预报.仿真结果可以表明,应用通过改进的BP神经网络进行炼钢精炼炉终点预报得到了很好的效果.

关键词: 钢包精炼, 电极控制, 神经网络, 终点预报

Abstract: Predicts the endpoint in ladle refining process by way of developing a relevant model through modified BP neural network in combination with the characteristics of ladle refining process. The prediction is based on such a concept that the parameters of the model are analyzed and determined in terms of the in site data recorded previously with other existing neural network models taken as reference, then the prediction model is set up. Other related data can therefore be predicted according to the model. Simulation results showed that the endpoint predicted by applying the modified BP neural network benefits much the ladle refining process.

中图分类号: