油气管道周向漏磁检测信号分析

用于检测管道腐蚀缺陷的漏磁检测方法已运用多年,但传统的轴向漏磁检测方法无法检测到狭长的轴向腐蚀缺陷,使用周向漏磁检测则能很好地弥补轴向漏磁检测的不足。周向漏磁检测及其信号分析在国内还处于起步阶段。采用ANSYS仿真软件建立了周向漏磁检测模型,并进行了电磁场模拟;对仿真模型提取的漏磁信号与腐蚀缺陷的尺寸信息进行了定性分析,提出应用BP神经网络定量分析油气管道腐蚀缺陷与漏磁信号的关系。结果表明：漏磁信号能定性地判断腐蚀缺陷,而使用BP神经网络方法可以定量地确定管道腐蚀缺陷尺寸,有助于提高检测的精度,同时也为油气管道安全评价提供了依据。

Analysis of the Circumferential Magnetic Flux Leakage (CMFL)Signal for Oil and Gas Pipeline

The magnetic flux leakage(MFL) testing method has long been used to detect corrosion defect of oil and gas pipelines.Applying circumferential MFL(CMFL) can make up for the deficiency of AMFL.Based on ANSYS software,the CMFL model has been built to simulate the magnetic field.The CMFL signal from the simulation model is analyzed of the dimensional parameters of corrosion defect,and BP neural network method is thus proposed to quantitatively analyze the relationship between CMFL signal and the dimensional feature of corrosion defect.The results show that MFL signal can qualitatively judge the feature of corrosion defect and the BP neural network method can quantitatively determine the dimension of corrosion defect and provide a reference for oil and gas pipeline safety assessment.