@ARTICLE{Halchenko_Volodymyr_Yakovych_Surrogate_2021,
 author={Halchenko, Volodymyr Yakovych and Trembovetska, Ruslana Volodymyrivna and Tychkov, Volodymyr Volodymyrovych},
 volume={vol. 70},
 number={No 4},
 journal={Archives of Electrical Engineering},
 pages={743-757},
 howpublished={online},
 year={2021},
 publisher={Polish Academy of Sciences},
 abstract={Existing scientific studies devoted to the design of eddy-current probes with a priori given configuration of the electromagnetic excitation field, which provide a uniform eddy current density distribution, consider a wide class of such, but are limited to the case when the probe is stationary relative to the testing object. Therefore, the actual problem is the synthesis of moving tangential eddy current probes with a frame excitation system that provides a uniform eddy current density distribution in the testing object, the solution of which is proposed in this study. A mathematical method for nonlinear surrogate synthesis of excitation systems for frame moving tangential surface eddy current probes, which implements a uniform eddy current density distribution of the testing zone object, is proposed. A metamodel of the volumetric structure of the excitation system of the frame tangential eddy current probe, applied in the process of surrogate optimal parametric synthesis, has been created. The examples of nonlinear synthesis of excitation systems using modern metaheuristic stochastic algorithms for finding the global extremum are considered. The numerical results of the obtained solutions of the problems are presented. The efficiency of the synthesized structures of excitation systems in comparison with classical analogs is shown on the graphs of the eddy current density distribution on the object surface in the testing zone.},
 type={Article},
 title={Surrogate synthesis of excitation systems for frame tangential eddy current probes},
 URL={http://www.czasopisma.pan.pl/Content/121557/PDF/art01.pdf},
 keywords={additive neural network regression, eddy current probe, stochastic optimization algorithm, surrogate optimization, uniformeddy current density distribution, velocity effect},
}