作者：陈俊杰

作者单位：电力规划设计总院, 北京 100120

关键词：漏磁检测;缺陷识别;分段处理;阈值截取;油气管道

摘要：

为解决油气管道漏磁检测数据量巨大所带来的处理难题，研究一种从漏磁检测数据中快速识别出待求解目标缺陷区域的检测方法。基于有限元仿真计算，对油气管道三维漏磁检测信号的特性进行研究，进而对检测数据进行分段阈值截取处理，并提出一种管道待求解缺陷区域的分段识别方法，可快速且准确地处理油气管道漏磁检测海量数据。基于实际油气管道的漏磁检测数据，对所提出的分段识别方法进行试验验证。试验结果表明：所提出的方法可准确识别出管道上的缺陷区域，既完整地包含缺陷及其附近区域，也不存在过量的无关区域，可有效地控制后续处理过程的数据量。

Segmentation identification method for defect area of MFL detection of oil and gas pipelines

CHEN Junjie

Electric Power Planning & Engineering Institute, Beijing 100120, China

Abstract: In order to solve the problem of the huge data of oil and gas pipelines magnetic flux leakage(MFL) detection, it is necessary to research a method to identify the target defect area to be solved from the MFL detection signals quickly. Based on the finite element simulation method, the characteristics of three-dimensional magnetic flux leakage detection signal for oil and gas pipelines are studied. Then, the detection data is processed with segmentation and threshold interception, and a segmentation method is proposed to identify the defect area quickly and properly. The experiment results based on real oil and gas pipelines demonstrate that the method can identify the pipeline defect area accurately, containing the defect and its nearby region without excess of irrelevant areas. Therefore, the proposed method can control the data quantity of the subsequent processing effectively.

Keywords: MFL detection;defect identification;segmentation processing;threshold interception;oil and gas pipelines

2017, 43(11): 1-7  收稿日期: 2017-02-09;收到修改稿日期: 2017-04-23

基金项目: 

作者简介: 陈俊杰(1988-),男,安徽六安市人,工程师,博士,主要从事现代电磁检测方法、电力系统相关问题研究。

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