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3D-FEM Computational and Inverse Problem in Nondestructive Evaluation Using Neural Networks for Detection of Cracks

S. Harzallah, M. L. Mimouni, S. Benissad, M. Chabaat


In this paper a new approach for computing fracture mechanics parameters by measuring and testing related Eddy currents is presented. This approach is based on the inverse eddy current. Simultaneous use of artificial neural networks (ANN) for the localization and the shape classification of defects can be described as the task of reconstructing the cracks and damage in the plate profile of an inspected specimen in order to estimate its material properties. This is accomplished by inverting eddy current probe impedance measurements which are recorded as a function of probe position, excitation frequency or both. In eddy current nondestructive evaluation, this is widely recognized as a complex theoretical problem whose solution is likely to have a significant impact on the characterization of cracks in materials. On the other side, a simulation by a numerical approach based on the finite element method is employed to detect cracks in materials and eventually to study their propagation. It is shown that this method has emerged as one of the most efficient technique for prospecting cracks in materials.

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