东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (5): 685-688.DOI: -

• 论著 • 上一篇    下一篇

软测量技术在铸锭裂纹预报中的应用

黄松林;崔建忠;   

  1. 东北大学材料电磁过程研究教育部重点实验室;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-05-15 发布日期:2013-06-22
  • 通讯作者: Huang, S.-L.
  • 作者简介:-
  • 基金资助:
    国家重点基础研究发展计划项目(2005CB623707)

Application of soft-sensing to prediction of ingot cracking trend

Huang, Song-Lin (1); Cui, Jian-Zhong (1)   

  1. (1) Key Laboratory of Electromagnetic Processing of Materials, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-05-15 Published:2013-06-22
  • Contact: Huang, S.-L.
  • About author:-
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摘要： 针对在铸锭成型过程中无法对裂纹的发展趋势进行在线预报的问题,以铝合金电磁半连续铸造为研究对象,采用软测量技术,通过选取可以直接在线测量的辅助变量,建立了一种基于多层前馈神经网络的裂纹软测量模型.该模型的输出为量化后的裂纹值,从而间接地在线测量了铸锭的裂纹量化值,并对裂纹的发展趋势进行了预报.仿真与实验结果表明:该模型的裂纹预报值和实际值吻合得较好,预报值能很好地反映实际裂纹的倾向,从而使得裂纹的在线预报与在线控制成为可能.

关键词: 软测量, 电磁铸造, 人工神经网络, 铝合金, 半连续铸造

Abstract: At present no measure is available to predict the trend of crack propagation online during ingot forming. To solve the problem, the soft sensing technique was applied to the semi-continuous electromagnetic casting process of Al-alloys, where the auxiliary parameters available to direct online sensing were chosen to develop a soft sensing model of cracks on the basis of multilayer feed forward neural network. The outputs from the model are the quantized values of crack, which means that the quantized values of ingot cracks are indirectly censored online and the trend of crack propagation is predicted. Experiment/simulation results revealed that the predicted values of crack from the model conform well the values actually measured, thus reflecting well the actual trend of cracks so as to make online prediction/control of cracks available.

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