中国机械工程 ›› 2010, Vol. 21 ›› Issue (10): 1200-1202,1207.

• 信息技术 • 上一篇    下一篇

万能轧制线高速钢轨轧制参数优化模型研究

郭煜敬1;谢志江1;王彦忠2;陶功明2;杨奇凡3
  

  1. 1.重庆大学机械传动国家重点实验室,重庆,400030
    2.攀枝花钢铁集团,攀枝花, 617062
    3.重庆邮电大学,重庆,400065
  • 出版日期:2010-05-25 发布日期:2010-06-02
  • 基金资助:
    国家重大科技专项基金资助项目(JW20*26017)
    National Science and Technology Major Project ( No. JW20*26017)

Study on Optimization Model of Rolling Parameters of High Speed Rail by Universal Mill

Guo Yujing1;Xie Zhijiang1;Wang Yanzhong2;Tao Gongming2;Yang Qifan3
  

  1. 1.State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030
    2.Panzhihua Steel Group Company,Panzhihua,Sichuan,617062
    3.Chongqing University of Posts and Telecommunications,Chongqing,400065
  • Online:2010-05-25 Published:2010-06-02
  • Supported by:
    National Science and Technology Major Project ( No. JW20*26017)

摘要:

针对高速钢轨万能轧制线多变量强耦合的特征,以钢轨断面轧制精度为目标,将优势区间控制算法与神经网络相结合,建立了钢轨轧制参数优化模型。将生产现场采集的大量轧制过程数据与钢轨断面检测数据建立对应关系,数据预处理后利用优势区间控制算法求出特定生产条件下的辊缝及轧制力的初始值,再利用神经网络对初始值进行偏差修正。实践证明,该模型能够减少主观因素的影响,提高钢轨的轧制精度。

关键词:

Abstract:

According to the characteristics of strong coupling of variables for universal rolling line of high speed rail,taking the rolling precision of rail section as the goal, it established an optimization model of rolling parameter of rail by combining the optimization-range algorithms with neural network.Corresponding relation among rolling course data and rail section gather data was set up, the dominant interzone was utilized to obtain initial value of roll gap and rolling strength under the particular working condition after preconditioning of the data, and the neural network was used to revise initial value. It has proved that this model can reduce the influence of the subjective factors and improve the rolling precision of the rail. 

Key words:  , rail, optimization-range, neural network, mill parameter

中图分类号: