| EFFECT OF COLD WORKING ON THE AGING PROPERTIES OF Cu-Cr-Zr-Mg ALLOY BY ARTIFICIAL NEURAL NETWORK |
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| 作者姓名： | J.H.Su H.J.Li Q.M.Dong P.Liu B.X.Kang B.H.Tian |
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| 作者单位： | [1]CollegeofMaterialsScienceandEngineering,NorthwesternPolytechnicalUniversity,Xi＇an710072,China [2]GollegeofMaterialsScienceandEngineering,HenanUniversityofScienceandTechnology,Luoyang471003,China |
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| 基金项目： | 国家高技术研究发展计划(863计划)，西北工业大学校科研和教改项目 |
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| 摘 要： | A developmental research has been carried out to deal with the high performance of Cu-Cr-Zr-Mg lead frame alloy by artificial neural network (ANN). Using the cold working to assist in the aging hardening can improve the the hardness and electrical conductivity properties of Cu-Cr-Zr-Mg lead frame alloy. This paper studies the effect of different extent of cold working on the aging properties by a supervised ANN to model the non-linear relationship between processing parameters and the properties. The back-propagation (BP) training algorithm is improved by Levenberg-Marquardt algorithm. A basic repository on the domain knowledge of cold worked aging processes is established via sufficient data mining by the network. The predicted values of the ANN coincide well with the tested data.So an important foundation has been laid for prediction and optimum controlling the rolling and aging properties of Cu-Cr-Zr-Mg alloy.
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| 关 键 词： | 老化特征 Cu-Cr-Zr-Mg合金 人工神经网络 冷加工工艺 |
EFFECT OF COLD WORKING ON THE AGING PROPERTIES OF Cu-Cr-Zr-Mg ALLOY BY ARTIFICIAL NEURAL NETWORK |
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| J.H.Su H.J.Li Q.M.Dong P.Liu B.X.Kang B.H.Tian.EFFECT OF COLD WORKING ON THE AGING PROPERTIES OF Cu-Cr-Zr-Mg ALLOY BY ARTIFICIAL NEURAL NETWORK[J].Acta Metallurgica Sinica(English Letters),2004,17(5):741-746. |
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| Authors: | JHSu HJLi QMDong PLIU BXKang BHTian |
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| Affiliation: | College of Materials Science and Engineering,Northwestern Polytechnical University,Xi＇an710072,China |
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| Abstract: | A developmental research has been carried out to deal with the high performance of Cu-Cr-Zr-Mg lead frame alloy by artificial neural network (ANN). Using the cold working to assist in the aging hardening can improve the the hardness and electrical conductivity properties of Cu-Cr-Zr-Mg lead frame alloy. This paper studies the effect of different extent of cold working on the aging properties by a supervised ANN to model the non-linear relationship between processing parameters and the properties. The back-propagation (BP) training algorithm is improved by Levenberg-Marquardt algorithm. A basic repository on the domain knowledge of cold worked aging processes is established via sufficient data mining by the network. The predicted values of the ANN coincide well with the tested data. So an important foundation has been laid for prediction and optimum controlling the rolling and aging properties of Cu-Cr-Zr-Mg alloy. |
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| Keywords: | Cu-Cr-Zr-Mg alloy cold working aging artificial neural network (ANN) |
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