碳钢大气腐蚀的大数据分析
Big Data Analysis of Atmospheric Corrosion of Carbon Steel
夏晨瀚 1杨小佳 2李清 2李晓刚 2杜楠1
作者信息
- 1. 南昌航空大学轻合金加工科学与技术国防重点学科实验室,南昌 330063
- 2. 北京科技大学新材料技术研究院,北京 100083
- 折叠
摘要
采用电偶型大气腐蚀监测传感器,在我国4种典型大气环境中对Q345碳钢的大气腐蚀行为进行了长期的大数据监测,同时记录了气温、相对湿度、以及空气污染指数等环境数据.讨论了在室外动态大气环境中碳钢腐蚀行为与各种环境因素之间的关系,利用机器学习获取环境因素中影响碳钢大气腐蚀行为的关键因素,建立了通过环境因素预测碳钢腐蚀行为的试验方法.结果表明:相对湿度和温度是影响碳钢腐蚀最主要的因素;机器学习可以通过环境因素预测碳钢的腐蚀趋势,但预测值与真实值之间还存在一定误差,需要对模型进行反复训练并对算法不断修正.
Abstract
Long-term big data monitoring of atmospheric corrosion behavior of Q345 carbon steel was carried out in 4 typical atmospheric environments in China by electric couple atmospheric corrosion monitoring sensor.Environmental data such as temperature,relative humidity,and air pollution index were recorded.The relationship between carbon steel corrosion behavior and environmental factors in outdoor dynamic atmosphere were investigated,and the key factors affecting the atmospheric corrosion behavior of carbon steel in the environmental factors were obtained by machine learning.A test method for predicting the corrosion behavior of carbon steel through environmental factors was established.The results show that relative humidity and temperature were the most important factors affecting the corrosion of carbon steel.Machine learning could predict the corrosion trend of carbon steel through environmental factors,but there was still a certain error between the predicted value and the actual value.So it was necessary to repeat training the model and constantly revise the algorithm.
关键词
大气腐蚀/碳钢/环境因素/腐蚀大数据Key words
atmospheric corrosion/carbon steel/environmental factor/corrosion big data引用本文复制引用
出版年
2024
NETL
NSTL
万方数据