支持向量回归预测不锈钢的点蚀电位

Prediction of pitting potential for stainless steel by support vector regression

点蚀是不锈钢的主要腐蚀类型之一,常用点蚀电位来评价不锈钢腐蚀的难易程度.点蚀电位会受到多方面因素的影响.基于不锈钢的元素成分和工艺参数,采用支持向量回归(support vector regression,SVR)算法建立了预测点蚀电位的模型.结果表明:独立测试集的相关系数达到0.97,均方根误差(root mean square error,RMSE)仅为0.07;通过Pearson相关分析和敏感性分析,元素Cr、Mo的含量和温度对点蚀电位的影响较大;当存在少量稀土元素时可以提高不锈钢的抗腐蚀能力.

Pitting corrosion is a primary corrosion type of stainless steel,and pitting potential is often used to evaluate the difficulty of corrosion of stainless steel.The pitting potential is affected by many factors.Based on the elemental composition and process parameters of stainless steel,support vector regression(SVR)was used to establish a model for predicting the pitting potential.The results showed that the correlation coefficient of the independent test set could reach 0.97 with the corresponding root mean square error(RMSE)of only 0.07.From the Pearson correlation analysis and sensitivity analysis,the element contents of Cr and Mo and the temperature had a crucial influence on the pitting potential,and a small amount of rare earth elements could improve the corrosion resistance of stainless steel.