Detection of natural gas pipeline defects using magnetic flux leakage measurements

Magnetic Flux Leakage (MFL) testing is the most widely used non-destructive techniques for the in-service inspection of oil and gas pipelines. This study presents novel approaches to detect defects by employing MFL signals. Estimating the number of defects, locations, and orientations from measurements is a typical inverse problem in electromagnetic non-destructive evaluations (NDE). A detection algorithm on axial flux is proposed for defect detection based on image processing approaches and morphological methods. Finally, the efficacy and accuracy of the proposed algorithm is validated through examinations on simulated defects and real experimental MFL data. Simulated defects are generated in presence of multiple uncertainties and noises; including the variation of the pipeline thickness, sensors liftoff, magnetization level, and shape irregularity.