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Evaluation of inverse algorithms in the analysis of magnetic flux leakage data

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4 Author(s)
J. Haueisen ; Biomagnetic Center, Friedrich-Schiller-Univ., Jena, Germany ; R. Unger ; T. Beuker ; M. E. Bellemann

We evaluate the use of linear and nonlinear inverse algorithms (maximum entropy method, low resolution electromagnetic tomography, L 1 and L2 norm methods) in the analysis of magnetic flux leakage (MFL) measurements commonly used for the detection of flaws and irregularities in gas and oil pipelines. We employed MFL data from a pipe with well-defined artificial surface breaking flaws at the internal and external wall. Except for the low-resolution electromagnetic tomography, all algorithms show, on average, similar accuracy in the flaw extent estimation. Maximum entropy and the L1 norm have a tendency to yield better results for smaller flaws, while the L2 norm performs slightly better for larger flaws. The errors of the flaw location estimation are comparable for the maximum entropy and the L2 norm algorithm. The L1 norm performs worse for those flaws situated on the internal pipe wall. Linear methods (L2 norm) are easier to implement and require less computation time than nonlinear methods (maximum entropy method, L1 norm). In conclusion, inverse algorithms potentially provide a powerful means for the detection and characterization of flaws in MFL data

Published in:

IEEE Transactions on Magnetics  (Volume:38 ,  Issue: 3 )