期刊论文

中文

中南林业科技大学学报

1673-923X

2011

31

12

183-186

10.14067/j.cnki.1673-923x.2011.12.007

基金项目：湖南省教育厅一般项目（09C1016） 中南林业科技大学青年科学研究基金项目（2009043B）

本校为第一机构

TC11钛合金在金属成形过程受载荷、温度、时间等因素的作用,其蠕变本构关系极其重要且复杂。针对这一情况,利用BP神经网络高精度的非线性拟合能力、记忆能力和很强的泛化能力,提出了一个基于BPNN(误差反向传播算法)的TC11钛合金蠕变本构关系模型。对关系模型进行训练、学习和仿真,并将其仿真结果与推广的Burgers模型推导的理论值和蠕变实验值进行误差分析,结果表明该模型具有很高拟合精度和一定的实际应用价值。

TC11 titanium alloy is influenced by load,temperature and time during the rheological forming process and its creep constitutive relationship is important and complex.Aimed to this case,a constitutive relationship model for TC11 titanium alloy based on BPNN（Back-Propagation Neuron Network） was proposed according to the high precision of nonlinear fitting,memory capacity and strong generalization capacity of BP neuron network.The model was trained,studied and simulated,and then the simulation results were compared to theoretical values obtaine...