Reconstruction of 3-D defect profiles from MFL signals using radial wavelet basis function neural network

This paper proposes an inversion procedure, based on radial wavelet basis function (RWBF) neural network, to reconstruct 3-D defect profiles from magnetic flux leakage (MFL) data. The architecture of the neural network, the adaptive training algorithm and the reconstruction process are presented. Defects reconstructed from both simulated and experimental MFL data, together with comparison with two other inversion methods, demonstrate the efficiency and accuracy of the proposed inversion procedure.