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基于BP神经网络的TC4钛合金超塑性变形后组织及性能预测研究
引用本文:陈明和,谢兰生,周建华,左敦稳,王珉.基于BP神经网络的TC4钛合金超塑性变形后组织及性能预测研究[J].机械工程材料,2003,27(12):4-6,19.
作者姓名:陈明和  谢兰生  周建华  左敦稳  王珉
作者单位:南京航空航天大学机电工程学院,江苏,南京,210016
摘    要:分别用Visual Fortran语言和MATLAB软件建立了TC4钛合金超塑性变形时变形参数与其力学性能和晶粒尺寸之间的BP神经N络模型,通过用较少的力学性能和晶粒尺寸的试验数据进行训练,进而对其性能进行预测。结果表明,BP神经网络用于材料超塑性变形后的力学性能及晶粒尺寸预测是可行的,其预测误差小于7%。

关 键 词:超塑性变形  TC4钛合金  BP神经网络  预测  组织  力学性能  晶粒尺寸
文章编号:1000-3738(2003)12-0004-03

Predicting Mechanical Properties and Microstructure of TC4 Alloy after Superplastic Forming based on BP Artificial Neural Network
CHEN Ming-he,XIE Lan-sheng,ZHOU Jian-hua,ZUO Dun-wen,WANG Min.Predicting Mechanical Properties and Microstructure of TC4 Alloy after Superplastic Forming based on BP Artificial Neural Network[J].Materials For Mechanical Engineering,2003,27(12):4-6,19.
Authors:CHEN Ming-he  XIE Lan-sheng  ZHOU Jian-hua  ZUO Dun-wen  WANG Min
Abstract:Based on BP artificial neural network, an investigation was carried out to predict mechanical properties and microstructure of TC4 alloy after superplastic forming. A BP artificial neural network model between superplastic deformation parameters and mechanical properties and microstructure of TC4 has been built, using Visual Fortran language and on the basis of Neural Network Toolbox in MATLAB software. It is trained for predicting the performance of TC4 alloy after superplastic deformation. The results show that BP artificial neural network can be used in predicting mechanical properties and grain size of materials after superplastic forming and its predicting error is less than 7%.
Keywords:superplasticity  TC4 titanium alloy  BP artificial neural network  predicting
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