Defect quantitative recognition technology of circumferential magnetic flux leakage inspection in pipeline

Through analysis of magnetic leakage field of circumferential magnetic flux leakage (MFL) inspection in pipeline, the peak-peak amplitude and the peak spacing of the radial MFL signal, the peak-peak amplitude and of the circumferential MFL signal, and the peak spacing of differential signal of the circumferential MFL signal are selected as the MFL signal features. The relationships between the defect geometry parameters(depth, width and length) and the MFL signal features are researched by simulation. By adopting the multiple linear regression theory, the regression equationes are established between the defect geometry parameters and the MFL signal features to implement the quantitative identification of the defect geometry parameters.