摘要
由高通量的腐蚀监测探头采集影响碳钢腐蚀的主要因素SO^(2)、温度、湿度和降雨信息,每分钟采集一条数据点,根据采集的数据,利用随机森林算法建立温度-湿度-SO^(2)-电流的关系模型。通过非试验地区的环境数据,即可预测该地区碳钢的腐蚀速率,从而大幅降低试验成本、缩短试验周期。
High-throughput corrosion monitoring probes are used to collect the data of main factors affecting carbon steel corrosion with one data point per minute,including SO2,temperature,humidity and rainfall.Based on the collected data,the random forest algorithm is applied to establish the relationship model of temperature-humidity-SO2-current.Therefore,the model can help to predict the corrosion rate of carbon steel in a non-test area according to the environmental data of this area,which can greatly reduce the test cost and shorten the test period.
作者
代芹芹
范益
蔡佳兴
DAI Qinqin;FAN Yi;CAI Jiaxing(Research Institute)
出处
《南钢科技与管理》
2021年第2期1-5,共5页
NISCO Technology and Management
关键词
碳钢
随机森林算法
模型
腐蚀速率
Carbon Steel
Random Forest Algorithm
Model
Corrosion Rate
