人工神经网络技术探讨碳钢、低合金钢的实海腐蚀规律  

ANALYSIS OF CORROSION DATA FOR CARBON STEEL ANDLOW-ALLOY STEELS IN SEAWATER BY ARTIFICIALNEURAL NETWORK

作　　者：孔德英[1] 宋诗哲[1] 

机构地区：[1]天津大学材料学院,天津300072

出　　处：《中国腐蚀与防护学报》1998年第4期289-296,共8页Journal of Chinese Society For Corrosion and Protection

基　　金：国家自然科学基金资助课题;金属腐蚀与防护国家重点实验室资助项目

摘　　要：根据金属海水腐蚀的特征,用人工神经网络技术分析碳钢、低合金钢海水腐蚀数据,建立了碳钢、低合金钢的腐蚀速率与合金成分及海水间的神经网络模型,可用于预测新钢种在其它海域中的腐蚀速率,并用所建模型分析了合金元素对腐蚀速率的影响。The corrosion data of carbon steel and low-alloy steels in seawater have been analyzed by means of artificial neural network. The non-linear relation models among corrosion rate and alloy compositions of carbon steel and low-alloy steels as well as main characteristics of seawater were established. As a result, the corrosion rate of unknown metal under different seawater conditions could be predicted by trained neural networks. Meanwhile, the effects of alloy compositions on corrosion rate were discussed using these models.

关 键 词：碳钢 低合金钢 人工神经网络 海水腐蚀 

分 类 号：TG172.5[金属学及工艺—金属表面处理] TP18[金属学及工艺—金属学]