基于双正交样条小波的输油管道焊接缺陷漏磁信号识别技术

Oil pipeline welding defect MFL signal recognition technology based on biorthogonal spline wavelet

针对输油管道焊接缺陷漏磁信号量大,无法精准检测漏磁信号磁场强度,影响识别效果的问题,提出基于双正交样条小波的输油管道焊接缺陷漏磁信号识别技术。应用双正交样条小波技术分解信号,采用稀疏矩阵求解器分解磁感应强度。计算连续小波变换系数和缺陷内漏磁场场磁导率,明确不同介质磁感应强度和场磁导率关系,识别凹、凸缺陷漏磁信号。实验结果表明,该技术凹形缺陷磁场强度检测结果只在峰值处出现了与实际数据最大为50 A/m的偏差,凸形缺陷磁场强度检测结果与实验数据一致。

In view of the fact that the magnetic flux leakage(MFL)signal of oil pipeline welding defects is large,and it is impossible to accurately detect the magnetic field intensity of the MFL signal,which affects the recognition effect,an oil pipeline welding defect MFL signal recognition technology based on biorthogonal spline wavelet is proposed.The biorthogonal spline wavelet technique is used to decompose the signal,and the sparse matrix solver is used to decompose the magnetic induction intensity.The coefficient of continuous wavelet transform(CWT)and the magnetic permeability of the leakage magnetic field inside the defect are calculated.The relationship between the magnetic induction intensity and magnetic permeability of different media are clarified.The leakage magnetic signal of concave and convex defects is identified.The experimental results show that the magnetic field intensity detection results of concave defects only show a maximum deviation of 50 A/m from the actual data at the peak,while that of the convex defects are consistent with the experimental data.