基于BP神经网络的铝青铜超塑性流变应力预测模型  

Predicting Model for Flow Stress of Aluminum Bronze in Superplastic State Based on BP Neural Network

作　　者：李合军[1] 陈拂晓[1] 杨永顺[1] 杨正海[1] 董文杰[1] 

机构地区：[1]河南科技大学材料科学与工程学院,河南洛阳471003

出　　处：《热加工工艺》2007年第5期88-90,共3页Hot Working Technology

基　　金：河南省科技攻关项基金资助项目(0624260035)

摘　　要：运用BP神经网络方法建立了铝青铜超塑性状态下流变应力与变形参数之间关系的预测模型,并利用该模型预测在不同拉伸条件下材料的流变应力。结果发现预测数据与试验数据吻合良好,误差小于8.5%。The prediction model which reflects the relation between flow stress and superplastic forming parameters of aluminum bronze was founded by the method of BP neural network, and using the model, the values of flow stress at different tensile conditions were predicted.The results show that the predicted values of the flow stress by the BP neural network are well in accordance with the test data and its errors are less than 8.5%.

关 键 词：BP神经网络 铝青铜 超塑性 流变应力 预测模型 

分 类 号：TG316.193[金属学及工艺—金属压力加工]