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基于人工神经网络的锻造性能预报的研究
引用本文:郭斌,戴护民.基于人工神经网络的锻造性能预报的研究[J].哈尔滨工业大学学报,1998,30(5):16-19.
作者姓名:郭斌  戴护民
作者单位:哈尔滨工业大学材料工程系
摘    要:应用Gleeble-1500热模拟试验机研究了1Cr18Ni9Ti的热墩成形过程,得出了流动应力随变形条件的变化规律,测量了空冷后试件的硬度。首次采用人工神经网络对锻造性能进行预报,采用不同的改进BP算法加速了网络的收敛,得到了较好的网络信息,对1Cr18Ni9Ti的锻造性能进行了较准确预报。

关 键 词:热力模拟  神经网络  锻造性能  预报  锻件  质量

Prediction of Forgability Based on Artificial Neural Network
Guo Bin,Dai Humin,Wu Shengxin.Prediction of Forgability Based on Artificial Neural Network[J].Journal of Harbin Institute of Technology,1998,30(5):16-19.
Authors:Guo Bin  Dai Humin  Wu Shengxin
Abstract:This paper studied the heat forming process of 1Cr18Ni9Ti by using Gleeble1500 Thermo simulation machine. The variation law of stress with forming condition has been established, and the hardness of air cooled workpiece measured. Forgability is predicted for the first time by applying artificial neural network and different improved BP algorithms have accelerated the convergence speed of neural network accurate forgability prediction has been achieved for 1Cr18Ni9Ti.
Keywords:Thermo  simulation  stress  artificial neural network  BP algorithm  
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