文献类型：期刊文献

中文题名：NiTi形状记忆合金高温变形神经网络研究

英文题名：Study on High Temperature Deformation of NiTi Shape Memory Alloy Based on BP Neural Network

作者：李爽[1];李在林[2]

第一作者：李爽

机构：[1]郑州旅游职业学院;[2]新乡学院物理与电子工程系

第一机构：郑州旅游职业学院,河南郑州450009

年份：2014

卷号：35

期号：2

起止页码：274-276

中文期刊名：铸造技术

外文期刊名：Foundry Technology

收录：CSTPCD;;北大核心:【北大核心2011】；

语种：中文

中文关键词：NiTi形状记忆合金;高温变形;BP神经网络

外文关键词：NiTi shape memory alloy;high temperature deformation;BP neural network

摘要：在Gleeble-1500热模拟机上进行热变形压缩试验,获得了NiTi形状记忆合金在不同应变速率和温度下的真应力-真应变实验数据及微观组织,根据实验数据基于BP神经网络建立模型对NiTi合金的高温变形进行预测。结果表明:随着应变速率的增加,TiNi合金的软化特性变得明显,模型的预测值与试验值误差较小,且预测精度和可靠度高。
The hot deformation compression test was performed on a Gleeble-1500 thermal-mechanical simulator, the true stresstrue strain experiment data and microstructure of NiTi shape memory alloy under different strain rate and temperature were obtained. According to the experiment data, the high temperature deformation of NiTi alloy was forecasted based on BP neural network model. The results show that, with the increase of strain rate, the softening characteristics of NiTi alloy become more obvious. the errors between the experimental values and the predicted values is small and is with high accuracy and reliability.