摘要
采用人工神经网络的方法,研究了挤压比、挤压比压和挤压温度对喷射沉积ZA35合金力学特性的影响,建立了喷射沉积ZA35合金热挤压工艺的人工神经网络模型。模型的输入参数为挤压比、挤压比压和挤压温度,输出参数为合金的抗拉强度和伸长率,该模型可以预测ZA35合金在不同热挤压工艺参数下的力学特性,也可以优化热挤压工艺参数。模型结果与实验结果吻合良好,推荐喷射沉积ZA35合金热挤压工艺参数:挤压比压为430 MPa,挤压比为12,挤压温度为260℃。
The effects of extrusion ratio, extrusion specific pressure and extrusion temperature on mechanical properties of spray deposited ZA35 alloy were studied by artificial neural network （ANN）, and an artificial neural network model of hot extrusion process was created. The input parameters of the model are extrusion ratio, extrusion specific pressure and extrusion temperature. The outputs are ultimate tensile strength and elongation. The model can be used for the prediction of properties of ZA35 alloy as functions of processing parameters. It can also be used for the optimization of processing parameters. The ANN results are in good agreement with experimental data, and the optimized hot extrusion processing parameters of extrusion ratio 12, extrusion specific pressure 430 MPa, extrusion temperature 260℃ are recommended.
出处
《兵器材料科学与工程》
CAS
CSCD
北大核心
2013年第5期48-51,共4页
Ordnance Material Science and Engineering
基金
辽宁省创新团队项目(2008T137)
关键词
ZA35合金
喷射沉积
热挤压工艺
人工神经网络
ZA35 alloy
spray deposition
hot extrusion process
artificial neural network （ANN）
