基于BP神经网络的TA15钛合金流变性能的预测与评估

Prediction and Evaluation on Rheological Properties of TA15 Titanium Alloy with BP Neural Network

利用热模拟机对TA15钛合金进行等温压缩实验,分析了TA15钛合金的热流变行为,并利用相关性系数和相对误差等统计标准评估并验证了BP神经网络模型的预测能力。结果表明:基于ANN建立的本构关系模型的预测值与实验值吻合良好,此模型能够用于描述TA15钛合金在热加工时各参数之间的高度非线性关系。

Isothermal compression deformation tests were conducted for TA15 titanium alloy by thermal simulator. The thermal rheological behavior of TA15 titanium alloy was analyzed. An artificial neural network（ANN） was trained with standard back-propagation learning algorithm, and a series of standards（the correlation coefficient and relative error） were used to evaluate and verify the predictive ability of the ANN model. The results show that the feed-forward back-propagation ANN model can accurately tracks the experimental data, which can describe the complicated nonlinear relationship among thermo dynamical parameters well.