SVM Corrosion Depth Prediction on Safety Management in Pipeline of Oil and Gas

摘要：

Pipeline ofoil and gas have an increase risk because of pipeline punctures and rupture caused by corrosion. Therefore, it is very important to have a reliable way for pipeline corrosion prediction. The corrosion depth prediction that base on the support vector machines(SVM) was introduced in this paper, and the corrosion data were obtained by electricity probe. The predicted results shows that prediction has a more high precision, and the error is less than 5％, as well as the average error is 3.33％. The prediction ways based the support vector machines is reasonable in the corrosion research, which can supply a scientific basis for pipeline safety management, service life prediction and repair.

关键词： corrosion depth support vector machines service life safety management forecasting

作者: RAO Guoran LIANG Ping LONG Xinfeng

作者单位: School of Electricity Power,South China University of Technology,Guangzhou 510640,Guangdong,China School of Chemical Engineering and Energy,South China University of Technology,Guangzhou 510640,Guan

会议类型: 国际会议

会议名称: The 2008 International Symposium on Safety Science and Technology(2008年安全科学技术国际会议)

会议地点: 北京

会议语种:英文

页码: 1192-1196

在线出版日期: 2008-09-24（万方平台首次上网日期，不代表论文的发表时间）