基于人工神经网络的奥贝球铁化学成分及热处理工艺优化设计  

OPTIMIZATION OF CHEMICAL COMPOSITION AND HEAT TREATMENT TO AUSTEMPERED DUCTILE IRON BASED ON ARTIFICIALNEURAL NETWORKS

作　　者：周小平[1] 

机构地区：[1]湖北工学院机械工程系,武汉430064

出　　处：《上海金属》2003年第4期33-35,共3页Shanghai Metals

摘　　要：以奥贝球铁的力学性能指标为输入 ,化学成分及热处理工艺为输出 ,建立了7× 5× 7结构的BP神经网络 ,经过训练学习 ,网络输出具有较高的精度 。A BP neural networks with the 7×5×7 structure was constructed by serving the mechanical properties of Austempered Ductile lron (ADI) as the input and the chemical composition and the heat treatment process as the output.After training and learning,the networks was possessed with better precise output and could be applied to the optimum design about the chemical composition of ADI and its heat treatment process.

关 键 词：奥贝球铁 化学成分 热处理工艺 优化设计 人工神经网络 球墨铸铁 

分 类 号：TG143.5[一般工业技术—材料科学与工程] TG164.2[金属学及工艺—金属材料]