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.
出处
《中国腐蚀与防护学报》
CAS
CSCD
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
关键词
碳钢
低合金钢
人工神经网络
海水腐蚀
Carbon steel, Low-alloy steel, Artificial neural network, Seawater corrosion
