基于漏磁内检测的管道环焊缝缺陷识别与判定  

Identification and determination of pipeline girth weld defect based on MFL ILI

作　　者：王富祥[1] 玄文博[1] 陈健[1] 王婷[1] 雷铮强[1] 杨辉[1] 

机构地区：[1]中国石油管道科技研究中心/中国石油天然气集团公司油气储运重点实验室

出　　处：《油气储运》2017年第2期161-170,共10页Oil & Gas Storage and Transportation

基　　金：中国石油天然气集团公司科研项目"油气管道输送实(试)验新方法和新技术开发";2015D-5008-39(GF);中国石油天然气集团公司科研项目"油气管道裂纹风险识别与检测评价技术前期研究";2016B-3107-0502

摘　　要：为了实现基于漏磁内检测的管道环焊缝缺陷的有效识别与判定,对环焊缝异常信号的特征及其影响因素进行了分析。通过漏磁信号有限元仿真分析与内检测牵拉试验,系统分析了管道磁化水平、传感器提离值、环焊缝余高,环焊缝缺陷形状、位置及开口方位等因素对缺陷漏磁场的影响,明确了环焊缝缺陷与漏磁信号特征之间的对应关系,提出了基于漏磁内检测信号的环焊缝缺陷分类方法。将环焊缝缺陷分成了4类,并给出了环焊缝缺陷的漏磁内检测检出率和识别准确率。现场开挖验证结果进一步验证了识别与分类判定结果的准确性,为基于漏磁内检测的环焊缝缺陷识别与判定技术工业化应用奠定了基础。In order to identify and determine effectively the girth weld （GW） defect of pipelines based on magnetic flux leakage （MFL） in-line inspection （ILl）, the GW features of abnormal signals and their influential factors were analyzed. Then, the effects of pipeline magnetization degree, sensor liftoff, GW remaining height, and shape, position and opening orientation of GW defect on the defect magnetic flux leakage field were investigated systematically by carrying out finite- element simulation analysis and in-line inspection traction test on MFL signals. As a result, the relationship between GW defects and MFL signal characteristics is clarified. And finally, the GW defect classification method based on MFL ILl signal was proposed. And accordingly, GW defects were classified into four types, and their detection ratio and identification precision ratio based on MFL ILl were also provided. The actual excavation results verify the identification and classification accuracy of this method. It provides the foundation for the industrial application of GW defect identification and determination technology based on MFL ILl.

关 键 词：环焊缝缺陷 漏磁内检测 缺陷识别 类型判定 

分 类 号：TE973.6[石油与天然气工程—石油机械设备]