喷射成形ZA35合金热处理工艺的人工神经网络优化

Optimization of heat treatment process for spray formed ZA35 alloy based on artificial neural network

采用人工神经网络方法,研究了固溶温度、固溶时间、时效温度和时效时间对喷射成形ZA35合金力学性能的影响,建立了喷射成形ZA35合金热处理工艺的人工神经网络模型。模型的输入参数为固溶温度、固溶时间、时效温度和时效时间,输出参数为合金抗拉强度和伸长率。该模型可以预测ZA35合金在不同热处理工艺参数下的力学性能,也可以优化热处理工艺参数。推荐喷射成形ZA35合金热处理工艺参数为370℃×4 h固溶处理+150℃×7 h时效处理。

Effects of heat treatment parameters including solid solution temperature , solid solution time, aging temperature and aging time on mechanical properties of spray formed ZA 35 alloy investigated by artificial neural network ( ANN ) .The input parameters of the neural network (NN) model were solid solution temperature, solid solution time, aging temperature and aging time.The outputs of the NN model were ultimate tensile strength and elongation of the alloy .The model can be used for the prediction of the properties of ZA 35 alloy as functions of heat treatment parameters .It can also be used for the optimization of the heat treatment parameters .The optimized heat treatment process was 370 ℃×4 h solid solution and 150 ℃×7 h aging.