基于ANN模型7050铝合金热轧制工艺研究  

Hot rolling process of 7050 aluminum alloy based on artificial neural network

作　　者：高奇峰[1] 吴雄喜[1] 

机构地区：[1]浙江工业职业技术学院,浙江绍兴312000

出　　处：《兵器材料科学与工程》2015年第2期81-84,共4页Ordnance Material Science and Engineering

基　　金：浙江省科技计划项目(2012C31018);绍兴公益性技术应用研究计划项目(2013B70008)

摘　　要：主要研究热轧制工艺对7050铝合金力学性能的影响。热轧制工艺考虑温度和热轧制的变形量,力学性能考虑屈服强度、抗拉强度、伸长率和硬度。通过拉伸实验采集不同热轧制情况下的力学性能指标,并观察相应情况下的金相结构;采用BP神经网络的方法对7050铝合金力学性能变化情况做出预测分析。结果表明:用BP神经网络的方法可以高精度地预测7050铝合金的力学性能,该方法能改善其热轧制工艺。The influence of rolling process on the mechanical properties of 7050 aluminum alloy was studied. Rolling technology including the temperature and the rolling deformation, mechanical performance including the yield strength, tensile strength, elongation and hardness were taken into consideration. Mechanical performance data were collected by tensile experiments under different rolling conditions, and the metallographic structures were observed as well. The mechanical properties of 7050 aluminum alloy were predicted using BP neural network method. The results show that BP neural network can well predict mechanical properties of 7050 aluminum alloy with high precision, and the method is helpful to improve the rolling technology.

关 键 词：热轧制工艺 力学性能 7050铝合金 BP神经网络 

分 类 号：TG115.53[金属学及工艺—物理冶金] TG146.23[金属学及工艺—金属学]