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材料工程  2013 

基于BP神经网络的AZ31镁合金加工图参数优化

DOI: 10.3969/j.issn.1001-4381.2013.09.006, PP. 27-31

Keywords: AZ31,流变应力,神经网络,加工图

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Abstract:

基于Gleeble-1500热模拟机测定的AZ31镁合金热压缩实验数据,通过BP神经网络对数据进行训练,建立了流变应力与应变、应变速率和温度相对应的预测模型,采用该模型的预测数据构造了AZ31的加工图。结果表明AZ31流变失稳区分布在低温高应变速率区和中温较低应变速率区,当温度为340~440℃、应变速率为0.01~0.02s-1时功率耗散因子较大,为加工性较好的区域;利用经过训练的神经网络模型,流变应力的网络预测值与实验值能够很好地吻合,其最大相对误差为6.67%;不同变形条件绘制的加工图表明AZ31是应变不敏感、但对温度和应变速率敏感的材料。

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