基于神经网络Ti-6Al-4V合金热循环下力学性能研究

Mechanical Properties of Ti-6Al-4V Alloy Based on BP Neural Network Under Thermal Cycling

测定了Ti-6Al-4V合金在不同热循环温度下的拉伸强度和拉伸塑性。结果表明:热循环对Ti-6Al-4V合金的拉伸强度有显著的影响,而对其拉伸塑性影响不明显;利用BP神经网络的相关理论和方法,建立了关于Ti-6Al-4V合金在热循环温度下的力学性能的BP神经网络模型,计算结果表明,预测误差均在5%以内,精度很高,可为进一步研究Ti-6Al-4V合金提供科学方法。

The tensile strength and tensile ductility of Ti-6A1-4V alloy were measured under thermal cycling temperatures. The results show that the tensile strength of the alloy is significantly influenced by thermal cycling temperature, but not as well as the tensile ductility. Using BP neural network theory and method, a BP neural network model on the mechanical properties of the alloy was established under different thermal cycling temperatures. The calculation results show that the prediction error is within 5% with high accuracy and the method can be used to research on Ti-6A1-4V alloy.