The analysis of magnetic flux leakage pipeline data involves both a scanning part for defect recognition and an analysis part to describe the defects found. In the analysis part, it is often important to discriminate between vicinal (close-by) defects and to examine these defects separately. We applied an inverse method (L_(2) minimum norm reconstruction) and a novel post-processing technique based on equivalent ellipsoids to resolve vicinal defects measured in a test pipeline. The magnetic fields were computed with the help of a boundary element model. We found that using inverse algorithms, thresholding, and post-processing techniques, the automatic discrimination of vicinal defects was possible in 15 out of 16 cases.
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