Oil-Gas Pipeline Magnetic Flux Leakage Testing defect reconstruction Based on Support Vector Machine

摘要：

Oil-gas pipelines Magnetic flux leakage (MFL) inspection, the reconstruction of defects shape is the key of pipeline inspection integrity evaluation, identifying the shape of defects would lead to a better maintenance plan. In this paper, Support Vector Machine (SVM) method is used in reconstruction of defects shape features. Collecting 450 terms data of 30 defects from field-testing, by training, establish MFL data library based on samples of three different shape defects MFL signal characteristics. MATLAB as a platform is made in the reconstruction experimental, to verify the accuracy of defect classification and defect Identification. The achieved accuracy is 92.7％ identifying the class of emulated defects over a set of 210 recordings. The experimental results show: the method has high accuracy and good generalization ability.

关键词： oil-gas pipelines MFL inspection defect reconstruction SVM

作者: Yang Lijian Liu Gang Zhang guoguang Gao Songwei

作者单位: School of information science & engineering Shenyang University of Technology Shenyang, china

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 1347-1350

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）