Serge Olszewski

Work place: Taras Shevchenko National University of Kyiv, Ukraine



Research Interests: Physics, Artificial Intelligence, Computer systems and computational processes, Computational Physics


Serge Olszewski is an associate professor at the Faculty of Radio Physics, Electronics and Computer Systems, Taras Shevchenko National University of Kyiv. He received his Doctor of engineering sciences at the Faculty of Radio Physics, Electronics, and Computer Systems, Taras Shevchenko National University of Kyiv. His research interests include artificial intelligence and plasma physics.

Author Articles
Digital Method of Automated Non-destructive Diagnostics for High-power Magnetron Resonator Blocks

By Serge Olszewski Yaroslav Tanasiichuk Viktor Mashkov Volodymyr Lytvynenko Irina Lurie

DOI:, Pub. Date: 8 Feb. 2022

The paper reveals the problem of the lack of standard non-destructive diagnostic methods for high-power microwave devices aimed at regeneration. The issue is understudied and requires further research. The conducted analysis of state of the art on the subject area exhibited that image processing was used to specify the examined object's target characteristics in a wide range of research. Having summarized the considered image comparison methods on the subject area of this work, the authors formulated several requirements for the selected image analysis method based on the automated non-destructive diagnosis of resonator units for high-power magnetrons. The primary requirement is using non-iterative algorithms; the second condition is a chosen method of image analysis, and the third option is the number of pixels for a processed image. It must significantly exceed the number of descriptors required for making a decision. Guided by the analysis results and based on the results of previous studies conducted by the authors, the algorithm for identifying a defect in the resonator unit of a microwave device based on the image of the frequency-azimuthal distribution for the probing field phase difference expressed by the Zernike moments is proposed. MATLAB R14a was used as a modeling environment. The descriptor vector was restricted to the Zernike moments, including the 7th order. The work is interdisciplinary and written at the intersection of technical diagnostics, microwave engineering, and digital image processing.

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