Research on High Temperature Mechanical Properties of Underaged Al-Cu-Mg-Ag Alloy Based on BP Neural Network
The effect of long thermal exposure on the mechanical properties and microstructures of an underaged Al-Cu-Mg-Ag alloy was studied by tensile test at room temperature. Using BP neural network method, a model of the heat exposure temperature, time and alloy mechanical properties was established. Based on experimental data, the mechanical properties of the alloy were forecasted by the BP neural network model. The results show that the BP neural network can better reflect the relationship between process parameters and experiment results with a high prediction accuracy and a strong generalization ability.