摘要
研究天然气管道CO_(2)腐蚀机理及预测模型,对管道进行异常预警,保障管道的安全运行。通过探讨天然气管道CO_(2)腐蚀机理,采取时空空间卷积方法及数据深度挖掘算法搭建管道CO_(2)抗腐蚀预测模型,从管道流量分布数据耦合度、管道CO_(2)腐蚀数据耦合度及数据前推估计敏感度来验证天然气管道CO_(2)抗腐蚀预测模型的仿真度,算法仿真环境下的数据结果高于BIM自带的数据结果。说明预测模型可以实现天然气管道腐蚀程度的异常预警,提高天然气管道的使用安全性。
The CO_(2) corrosion mechanism and prediction model of natural gas pipeline are studied, and the abnormal warning of pipeline is carried out to ensure the safe operation of pipeline. By discussing the CO_(2) corrosion mechanism of natural gas pipelines, the spatiotemporal convolution method and data deep mining algorithm are adopted to build a pipeline CO_(2) corrosion resistance prediction model, and the simulation degree of the natural gas pipeline CO_(2) corrosion resistance prediction model is verified from the coupling degree of pipeline flow distribution data, the coupling degree of pipeline CO_(2) corrosion data and the sensitivity of data forward estimation, and the data results in the algorithm simulation environment are higher than the data results that come with BIM. It is explained that the prediction model can realize the abnormal warning of the corrosion degree of natural gas pipelines and improve the safety of natural gas pipelines.
作者
陈永清
CHEN Yong-qing(Jiangxi Provincial Natural Gas Group Co.,Ltd.Pipeline Branch,Nanchang 330000)
出处
《环境技术》
2022年第6期143-146,166,共5页
Environmental Technology
关键词
预测模型
天然气
仿真度
数据耦合
predictive models
natural gas
degree of simulation
data coupling
