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Magnetic flux simulations were utilized in a novel magnetic measurement method performed for the detection of local thinning of ferromagnetic plates. It was shown by numerical simulation, how parameters affect detectability of the defects. Linear relationship was found between the evaluated parameters and size of the artificial slot. Good correlation was found between theoretical and experimental results. [ABSTRACT FROM AUTHOR]

An adaptive sampling method based on simplex-mesh refinement is proposed for creating a database that facilitates the inverse problem solution in NDT. The resulting database is used as a generic interpolator of the forward problem. In order to obtain optimal sampling for the purpose of interpolation, physically based mesh generation technique relying on spring analogy is utilized. The method is tested with a four-parameter crack reconstruction problem. It is demonstrated that the optimized database provides high interpolation quality comparing to regular grid databases. [ABSTRACT FROM AUTHOR]

Neural network is applied for the non-destructive evaluation of in-material defects based on the measured or simulated data of an eddy-current testing experiment. The network is trained with the data measured for suitably selected defect prototypes, so that this selection constitute a consistent representation of the forward problem. This network performs in defect reconstruction better, than those networks trained with randomly or regularly selected defect prototypes of about the same number. [ABSTRACT FROM AUTHOR]

The reconstruction problem of porous silicon (PS) structures is investigated by means of a specific optimized inversion database. The database is supported by a generic n-dimensional adaptive anisotropic simplex mesh. The proposed mesh database carries additional information on the inverse problem: the number of database nodes indicates the relevance of the model used for the reconstruction, while the mesh structure reflects the capabilities of the inversion as well as the role of the chosen model parameters. Based on this information one is able to propose an optimal model for the given inverse problem. [ABSTRACT FROM AUTHOR]

A procedure developed for the calibration of a magnetic sensor in spatially strongly inhomogeneous magnetic field is presented in this paper. Assuming that the sensor is linear and it does not significantly disturb the magnetic field to be measured, its output signal is approximated as the weighted sum of the field values calculated theoretically around the sensor. The weighting coefficients are obtained by finding the best fit of the actual experimental output and the theoretical prediction of the measured field in the least square sense. Using the presented procedure, sensors can be calibrated for the measurement of spatially strongly inhomogeneous magnetic fields, consequently such sensors can be applied to get the field distribution map of inhomogeneous fields. [Copyright &y& Elsevier]