TY - CHAP
T1 - Defect detection and width estimation in natural gas pipelines using MFL signals
AU - Kandroodi, Mojtaba Rostami
AU - Shirani, Farshad
AU - Araabi, Babak Nadjar
AU - Ahmadabadi, Majid Nili
AU - Bassiri, Maisam Mansoob
PY - 2013/6/23
Y1 - 2013/6/23
N2 - Magnetic Flux Leakage (MFL) testing is the most widely used non-destructive techniques for the in-service inspection of oil and gas pipelines. In this study, a novel approach for detecting and estimating the width of defects by employing MFL signals is presented. Estimating the locations of defects and profiles of lengths, widths, and depths of defects from measurements is a typical inverse problem in electromagnetic non-destructive testing. In this study, defect parameters are estimated in two separate consecutive steps. In the first step, a detection algorithm based on image processing approaches is applied on axial flux to estimate the numbers of defects, locations, and orientations of defects. Then, to estimate widths of defects, an inversion procedure based on 2D signal processing is applied on radial flux corresponding to areas detected in previous step. 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. © 2013 IEEE.
AB - Magnetic Flux Leakage (MFL) testing is the most widely used non-destructive techniques for the in-service inspection of oil and gas pipelines. In this study, a novel approach for detecting and estimating the width of defects by employing MFL signals is presented. Estimating the locations of defects and profiles of lengths, widths, and depths of defects from measurements is a typical inverse problem in electromagnetic non-destructive testing. In this study, defect parameters are estimated in two separate consecutive steps. In the first step, a detection algorithm based on image processing approaches is applied on axial flux to estimate the numbers of defects, locations, and orientations of defects. Then, to estimate widths of defects, an inversion procedure based on 2D signal processing is applied on radial flux corresponding to areas detected in previous step. 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. © 2013 IEEE.
KW - Magnetic flux leakage
KW - axial flux
KW - image processing
KW - non-destructive testing
KW - radial flux
KW - width estimation
UR - https://www.mendeley.com/catalogue/fe755eca-fbdf-3a16-a6e4-e99abaa47fc0/
U2 - 10.1109/ASCC.2013.6606345
DO - 10.1109/ASCC.2013.6606345
M3 - Chapter
SN - 9781467357692
T3 - 2013 9th Asian Control Conference, ASCC 2013
BT - 2013 9th Asian Control Conference, ASCC 2013
ER -