| Simulation of aging process of lead frame copper alloy by an artificial neural network |
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| 作者姓名： | 苏娟华 董企铭 刘平 李贺军 康布熙 |
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| 作者单位： | Institute of Materials Science and Engineering，Institute of Materials Science and Engineering，Institute of Materials Science and Engineering，Institute of Materials Science and Engineering，Institute of Materials Science and Engineering Northwestern Polytechnical University，Xi′an 710072，China，Institute of Materials Science and Engineering，Henan University of Science and Technology，Luoyang 471003，China，Henan University of Science and Technology，Luoyang 471003，China，Henan University of Science and Technology，Luoyang 471003，China，Northwestern Polytechnical University，Xi′an 710072，China，Henan University of Science and Technology，Luoyang 471003，China |
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| 基金项目： | Project(2 0 0 2AA3 3 1112)supportedbytheNationalAdvancedMaterialsCommitteeofChina,Project(0122021300)supportedbytheMajorScienceandTechnologyProjectofHenanProvince,China |
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| 摘 要： | 1 INTRODUCTIONThefunctionsofleadframeinelectronicpackingareprovidingchannelsforelectronicsignalsbetweendevicesandcircuits ,andfixingdevicesoncircuitboards.Leadframealloysarerequiredtohavehighstrengthandgoodformabilityaswellashighelectri calandthermalconductivity .Cu basealloysarethemostpopularleadframealloysandareusedinplasticpackagingapplicationduetotheirhighthermalandelectricalconductivityaswellashighstrength13] .Theaginghardening processinfabricationofleadframecopperalloymakesitpossi…
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Simulation of aging process of lead frame copper alloy by an artificial neural network |
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| SU Juan-hua.Simulation of aging process of lead frame copper alloy by an artificial neural network[J].Transactions of Nonferrous Metals Society of China,2003,13(6). |
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| Authors: | SU Juan-hua |
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| Abstract: | The aging hardening process makes it possible to get higher hardness and electrical conductivity of lead frame copper alloy. The process has only been studied empirically by trial-and-error method so far. The use of a supervised artificial neural network(ANN) was proposed to model the non-linear relationship between parameters of aging process with respect to hardness and conductivity properties of Cu-Cr-Zr alloy. The improved model was developed by the Levenberg-Marquardt training algorithm. A basic repository on the domain knowledge of aging process was established via sufficient data mining by the network. The results show that the ANN system is effective and successful for predicting and analyzing the properties of Cu-Cr-Zr alloy. |
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| Keywords: | copper alloy aging process Levenberg-Marquard algorithm artificial neural network |
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