Introduction. The work is devoted to metamodels creation of surface circular concentric eddy current probe. Formulation of the problem. In the problem of surface circular concentric eddy current probe synthesis in the general formulation, apriori given desired eddy currents density distribution in the control zone was used. The realization of the optimal synthesis problem involves a multiple solution to the analysis problem for each current structure of numerical calculations excitation, which are very costly in terms of computational and time costs, which makes it impossible to solve the synthesis problem in the classical formulation. By solving the critical resource intensiveness problem, there is the surrogate optimization technology using of that uses the surface circular concentric eddy current probe metamodel, which is much simpler in realization and is an approximation of the exact electrodynamic model. Goal. Creation of surface circular concentric eddy current probe RBFmetamodels, which can be used to calculate eddy currents density distribution in the control zone and suitable for use in optimal synthesis problems. Method. To develop an approximation model, a mathematical apparatus for artificial neural networks, namely, RBF-networks, has been used, whose accuracy has been increased with the help of the neural networks committee. Correction of errors in the committee was reduced by applying the bagging procedure. During the network training the regularization technique is used, which avoids re-learning the neural network. The computer experiment plan was performed using the Sobol LP-sequences. The obtained multivariable regression model quality evaluation was performed by checking the response surface reproducibility correctness in the entire region of variables variation. Results. The modelling of eddy currents density distribution calculations on exact electrodynamic mathematical models in the experimental plan points are carried out. For the immovable and moving surface circular concentric eddy current probe, RBF-metamodels were constructed with varying spatial coordinates and radius. Scientific novelty. Software was developed for eddy currents density distribution calculation in the surface circular concentric eddy current probe control zone taking into account the speed effect on exact electrodynamic mathematical models and for forming experiment plan points using the Sobol LP-sequences. The geometric surface circular concentric eddy current probe excitation structures models with homogeneous sensitivity for their optimal synthesis taking into account the speed effect are proposed. Improved computing technology for constructing metamodels. The RBF-metamodels of the surface circular concentric eddy current probe are built and based on the speed effect. Practical significance. The work results can be used in the surface circular concentric eddy current probe synthesis with an apriori given eddy currents density distribution in the control zone.References 22, tables 6, figures 8. Key words: surface e...

Uniform multi-dimensional designs of experiments for effective research in computer modelling are highly demanded. The combinations of several one-dimensional quasi-random sequences with a uniform distribution are used to create designs with high homogeneity, but their optimal choice is a separate problem, the solution of which is not trivial. It is believed that now the best results are achieved using Sobol’s LPτ-sequences, but this is not observed in all cases of their combinations. The authors proposed the creation of effective uniform designs with guaranteed acceptably low discrepancy using recursive Rd-sequences and not requiring additional research to find successful combinations of vectors set distributed in a single hypercube. The authors performed a comparative analysis of both approaches using indicators of centred and wrap-around discrepancies, graphical visualization based on Voronoi diagrams. The conclusion was drawn on the practical use of the proposed approach in cases where the requirements for the designs allowed restricting to its not ideal but close to it variant with low discrepancy, which was obtained automatically without additional research.

A new multiparameter express method for eddy-current measurement of radial near-surface profiles of electrophysical parameters of cylindrical control objects with a priori accumulation of information about them is proposed. The method combines in-situ measurements and model calculations using high-performance computing technologies of artificial intelligence based on neural networks, carried out both in advance in order to obtain specific information about objects, and directly in the process of performing measurements to quickly obtain a result. Mathematically, the method is based on the unique ability to quickly solve Maxwell's equations as a result of its approximation by deep neural networks without actually explicitly executing this solution. This allows deep learning to be used not only in the forward direction, but also in the opposite direction, i.e. apply to solve inverse measuring problems. The method is universal and can be extended to multiparameter measurement control with simultaneous additional determination of the diameter of a cylindrical object. The adequacy of the proposed method by numerical experiments is proved; examples of the implementation of all stages of its application are given. Algorithms and a complex of programs in the Python 3 environment have been created, which make it possible to practically implement the method. The profile measurement accuracy established on model calculations is characterized by maximum relative errors not exceeding 0.5%, provided that the probe signal is perfectly fixed. It is possible to generalize the use of the proposed method to similar eddy current measurements with surface probes of profiles of material parameters of flat objects.

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A method for nonlinear surrogate synthesis of surface eddy current probes with a volumetric structure of the excitation system was proposed. This method a priori provides a given uniform distribution of eddy current density in the testing object area where the measuring coil is located. The implementation of the task using modern metaeuristic stochastic algorithms for finding the global extremum was achieved. For the effective usage of such algorithms, taking into account the effect of velocity, metamodels of eddy current probe were preliminarily created. They were built using a productive approximation technique based on artificial radial-basis neural networks with a Gaussian activation function. Acceptable accuracy of metamodels was achieved due to the simultaneous application of the search area decomposition technologies and plural neural networks based on the techniques of associative machines with group methods for obtaining a solution. For metamodels creation a multidimensional computer experiment design with high homogeneity was used on the basis of the parameterless additive Rd-Kronecker sequence. Numerical experiments to determine the eddy current density distributions which formed by synthesized excitation structures were carried out. The advantages of using a three-dimensional structure excitation system in comparison with classical and planar ones in terms of increasing the width of the testing zone, which is characterized by uniform sensitivity, were shown. Examples of practical implementation of an excitation system with a volumetric structure for an surface eddy current probe are given. References 13, figures 8, table 1.