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应用科学学报 ›› 2001, Vol. 19 ›› Issue (4): 353-356.

• 论文 • 上一篇    下一篇

铝合金凝固晶粒尺寸的人工神经网络研究

訾炳涛1, 姚可夫1, 崔建忠2, 巴启先2   

  1. 1. 清华大学机械工程系, 北京 100084;
    2. 东北大学材料与冶金学院, 辽宁沈阳 110004
  • 收稿日期:2000-09-17 修回日期:2001-02-23 出版日期:2001-12-31 发布日期:2001-12-31
  • 作者简介:訾炳涛(1965-),男,陕西西安人,博士.
  • 基金资助:
    国家重大基础研究发展规划基金资助项目(G199906490005)

A Study on the Artificial Neural Network Model of the Solidified Grain Size of Al- alloy

ZI Bing-tao1, YAO Ke-fu1, CUI Jian-zhong2, BA Qi-xian2   

  1. 1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
    2. School of Materials and Metallurgy, Northeastern University, Shenyang 110004, China
  • Received:2000-09-17 Revised:2001-02-23 Online:2001-12-31 Published:2001-12-31

PDF

81

被引次数

5

摘要： 建立了强脉冲电磁场作用下铝合金凝固组织晶粒尺寸的人工神经网络BP算法模型.用该模型进行的模拟结果和实验数据吻合得较好.研究表明,用这一方法可对脉冲电磁场作用下的凝固组织晶粒尺寸进行预测,为优化实验设计提供了简便实用的方法和手段.

关键词: 人工神经网络, BP算法模型, 凝固组织晶粒尺寸

Abstract: A BP algorithmic model was established for the artificial neural network of the grain size of Al-alloy's solidification structure under the action of strong pulse electromagnetic field. The simulating results were in agreement with the experimental results. It was shown that this BP algorithmic model of artificial neural network could be used to control the parameters and predict the solidified grain size under the action of strong pulse electromagnetic field. It provides us with an easy and practical method and means for optimizing experimental design.

Key words: grain size of solidification structure, artificial neural network, BP arithmetic model

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