Вісник Черкаського державного технологічного університету (Oct 2019)
ESTIMATION OF ACCURACY OF NEURO-NETWORK METAMODELS OF SURFACE EDDY CURRENT PROBES
Abstract
For the problem of synthesis of an eddy current probe with a homogeneous sensitivity zone, its RBF-metamodels which have high computational efficiency are created. These metamodels can be used to design a probe with a given distribution of the density of eddy currents at testing points of the space located on the surface of the conductive object in the testing area of the probe. The excitation coil of a concentric surface eddy current probe is represented by an actuator which is powered by an alternating current and located above the testing object with constant electrophysical parameters. The obtained metamodels are checked for adequacy and informativeness on a complex of statistical indicators with an objective estimation of their statistical significance. At the approximation of the response surface, the computer experiment plan was used, namely, the multidimensional search space was filled with points generated by means of LPτ-sequences that were evenly located on the response surface. The reproducibility of the review surface is checked using the resulting metamodel throughout the modeling area. A reasonable approximation error has been achieved. The results of numerical experiments show the effectiveness of the use of RBF-metamodel for the response surface approximation. The resulting metamodels have an average model error of 6.76 % for the first subregion, 4.8 % for the second and 4.78 % for the third one. Created metamodel is adequate according to Fisher criterion; informative on the coefficient of determination and significantly reliable. At the same time, it allows to reduce the workload of calculations in the tasks of computer designing of eddy current probes. This opens up new possibilities for the synthesis of surface eddy current probes – both parametric and structural-parametric ones.
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