基于神经网络的铸钢奥氏体形成温度预测  

Prediction on Austenite Formation Temperature of Cast Steel Based on Neural Network

作　　者：范伟[1] 牛悦娇[2] 

机构地区：[1]衢州学院,浙江衢州324000 [2]河北联合大学,河北唐山063009

出　　处：《铸造技术》2014年第2期290-292,共3页Foundry Technology

摘　　要：以铸钢奥氏体形成的两个关键温度为研究对象,利用BP人工神经网络成功预测了奥氏体开始转变温度、全部转变结束温度,分析了合金元素对两个温度点的影响。方法弥补了传统经验公式预测的缺陷,是一种可靠的奥氏体形成温度预测方法。Taking two key critical temperature of forming austenite in cast steel as research object, using BP artificial neural network, the start transform temperature and the end transform temperature of austenite were predicted, and the effect of alloying elements on the two temperature points was analyzed. The method makes up the predict defects of traditional empirical formulas, is a reliable prediction method of austenite formation temperature.

关 键 词：人工神经网络 奥氏体 合金元素 

分 类 号：TG156[金属学及工艺—热处理] TG113[金属学及工艺—金属学]