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PurposeThe purpose of this paper is to propose modelling 3D eddy current non destructive testing (EC NDT) problems by the finite volume method (FVM). Furthermore, the movement of the probe coil is taken into account.Design/methodology/approachThe nonconforming mesh technique is used to handle the displacement of the probe coil. Thus, the whole problem is divided into two parts; moving part (probe coil) and fixed part (specimen with crack), and then each part meshes independently. A computer code is built under Matlab program to generate 3D nonconforming mesh, to calculate magnetic and electric potentials and to evaluate the impedance change of the coil due to the presence of the crack.FindingsThe JSAEM No. 6 problem is used to test the proposed method. The calculated values of the impedance change of the probe coil due to the presence of crack, shows the efficiency of the developed software. A small difference is obtained between calculated values and measured values.Originality/valueThe paper introduces the FVM in solving EC NDT problems where the probe displacement is taken into account.

An improved method which can analyze the eddy current density in conductor materials using finite volume method is proposed on the basis of Maxwell equations andT-formulation. The algorithm is applied to solve 3D electromagnetic nondestructive evaluation (E’NDE) benchmark problems. The computing code is applied to study an Inconel 600 work piece with holes or cracks. The impedance change due to the presence of the crack is evaluated and compared with the experimental data of benchmark problems No. 1 and No. 2. The results show a good agreement between both calculated and measured data.

<p>Electrical energy production based on wind power is gaining area as renewable resources in the recent years because it gets clean energy with minimum cost. The major challenge for wind turbines is the electrical and the mechanical failures which can occur at any time causing damages and therefore it leads to machine downtimes and to energy production loss. To avoid this problem, several methods have been developed and used. In this paper, we proposed an expert system based on fuzzy logic which can detect and diagnosis DFIG’s faults via the Stator current’s signatures. The fuzzy inference system exploits the root mean square values of the stator’s currents according to expert’s rules to diagnosis the DFIG’s state. The smart proposed expert system is verified using simulations done under Matlab/Simulink. The obtained results are very interesting and show the efficiency of the proposed strategy.</p>

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