Indirect simultaneous eddy-current measurements of subsurface profiles of electrophysical properties in planar objects using a priori knowledge about them

• Autorzy: Halchenko Volodymyr Ya. , Trembovetska Ruslana , Tychkov Volodymyr

Identyfikatory

DOI

10.24425/mms.2025.152781

• Języki publikacji: EN

Abstrakty

EN

An eddy-current method of simultaneous indirect measurements of distributions of electrical conductivity and magnetic permeability in the subsurface zone of planar objects is proposed, based on a surrogate optimization algorithm using neural network metamodels of reduced dimensionality. Reduction of their dimensions and the space for finding an extremum is performed using the Kernel PCA method, which involves nonlinear transformations as a result of computational operations with the Gaussian kernel function. The construction of metamodels involved the use of deep learning methods. The peculiarities of metamodels include the performance of two functions, in particular, providing low-cost efficient computing and accumulating additional a priori information about the measurement process, which is digitally entered into the design of the experiment determining the training samples for training of deep neural networks. Taken as a whole, it made it possible to achieve higher accuracy characteristics of indirect measurements.

Słowa kluczowe

EN

indirect measurements; electrophysical property profiles; surrogate optimization; reduced dimension metamodel

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2025
• Tom: Vol. 32, nr 1
• Strony: 1--15
• Opis fizyczny: Bibliogr. 38 poz., rys., tab., wykr., wzory

Twórcy

autor

Halchenko Volodymyr Ya.

• Cherkasy State Technological University, Instrumentation, Mechatronics and Computer Technologies Department, Blvd. Shevchenkà, 460, 18006, Cherkasy, Ukraine

autor

Trembovetska Ruslana

• Cherkasy State Technological University, Instrumentation, Mechatronics and Computer Technologies Department, Blvd. Shevchenkà, 460, 18006, Cherkasy, Ukraine

• https://orcid.org/0000-0002-2308-6690

autor

Tychkov Volodymyr

• Cherkasy State Technological University, Instrumentation, Mechatronics and Computer Technologies Department, Blvd. Shevchenkà, 460, 18006, Cherkasy, Ukraine

• https://orcid.org/0000-0001-9997-307X

Bibliografia

• [1] Bowler, N. (2019). Eddy-Current Nondestructive Evaluation. In Springer Series in Measurement Science and Technology. Springer New York. https://doi.org/10.1007/978-1-4939-9629-2
• [2] Sabbagh, H. A., Murphy, R. K., Sabbagh, E. H., Aldrin, J. C., & Knopp, J.S. (2013). Computational Electromagnetics and Model-Based Inversion. In Scientific Computation. Springer New York. https://doi.org/10.1007/978-1-4419-8429-6
• [3] Liu, G. R., & Han, X. (2003). Computational Inverse Techniques in Nondestructive Evaluation. CRC press. https://doi.org/10.1201/9780203494486
• [4] Lu, M. (2018). Forward and Inverse Analysis for Non-destructive Testing Based on Electromagnetic Computation Methods (Publication No. 10983954) [Doctoral dissertation, University of Manchester]. ProQuest Dissertation & Theses.
• [5] Yi, Q., Tian, G. Y., Malekmohammadi, H., Laureti, S., Ricci, M., & Gao, S. (2021). Inverse reconstruction of fibre orientation in multilayer CFRP using forward FEM and eddy current pulsed thermography. NDT & E International, 122, 102474. https://doi.org/10.1016/j.ndteint.2021.102474
• [6] Xu, J., Wu, J., Xin, W., & Ge, Z. (2020). Fast measurement of the coating thickness and conductivity using eddy currents and plane wave approximation. IEEE Sensors Journal, 21(1), 306-314. https://doi.org/10.1109/JSEN.2020.3014677
• [7] Tesfalem, H., Peyton, A. J., Fletcher, A. D., Brown, M., & Chapman, B. (2020). Conductivity profiling of graphite moderator bricks from multifrequency eddy current measurements. IEEE Sensors Journal, 20(9), 4840-4849. https://doi.org/10.1109/JSEN.2020.2965201
• [8] Hampton, J., Fletcher, A., Tesfalem, H., Peyton, A., & Brown, M. (2022). A comparison of non-linear optimisation algorithms for recovering the conductivity depth profile of an electrically conductive block using eddy current inspection. NDT & E International, 125, 102571. https://doi.org/10.1016/j.ndteint.2021.102571
• [9] Tesfalem, H., Hampton, J., Fletcher, A. D., Brown, M., & Peyton, A. J. (2021). Electrical resistivity reconstruction of graphite moderator bricks from multi-frequency measurements and artificial neural networks. IEEE Sensors Journal, 21(15), 17005-17016. https://doi.org/10.1109/JSEN.2021.3080127
• [10] M. Lu, X. Meng, R. Huang, L. Chen, A. Peyton and W. Yin. (2021). Measuring Lift-Off Distance and Electromagnetic Property of Metal Using Dual-Frequency Linearity Feature. In IEEE Transactions on Instrumentation and Measurement, 70, 1-9, 6001409. https://doi.org/10.1109/TIM.2020.3029348
• [11] Halchenko, V. Y., Trembovetska, R., Tychkov, V., Tychkova, N. (2024). Surrogate methods for determining profiles of material properties of planar test objects with accumulation of a priori information about them. Archives of Electrical Engineering, 183-200. https://doi.org/10.24425/aee.2024.148864
• [12] Halchenko, V. Y., Trembovetska, R., Tychkov, V., & Tychkova, N. (2024). Reconstruction of Electrophysical Parameter Distribution During Eddy Current Measurements of Structural Features of Planar Metal Objects. Latvian Journal of Physics and Technical Sciences, 61(3), 61-75. https://doi.org/10.2478/lpts-2024-0021
• [13] Kozieł, S., Ogurtsov, S., & Bekasiewicz, A. (2016). Suppressing side-lobes of linear phased array of micro-strip antennas with simulation-based optimization. Metrology and Measurement Systems, 23(2), 193-203. https://doi.org/10.1515/mms-2016-0022
• [14] Halchenko, V., Trembovetska, R., Tychkov, V., Sapogov, M., Gromaszek, K., Smailova, S., & Luganskaya, S. (2021). Additive neural network approximation of multidimensional response surfaces for synthesis of eddy-current probes. Przegląd Elektrotechniczny, 97(9), 46-49. https://doi.org/10.15199/48.2021.09.10
• [15] Halchenko, V. Y., Trembovetska, R. V., Tychkov, V. V. (2019). Development of excitation structure RBF-metamodels of moving concentric eddy current probe. Electrical Engineering & Electromechanics, (2), 28-38. https://doi.org/10.20998/2074-272X.2019.2.05
• [16] Uzal, E. (1992). Theory of Eddy Current Inspection of Layered Metals (Publication No. 9335046) [Doctoral dissertation, Iowa State University]. ProQuest Dissertation & Theses.
• [17] Lei, Y. Z. (2018). General series expression of eddy-current impedance for coil placed above multi-layer plate conductor. Chinese Physics B, 27(6), 060308. https://doi.org/10.1088/1674-1056/27/6/060308
• [18] Zhang, J., Yuan, M., Xu, Z., Kim, H. J., & Song, S. J. (2015). Analytical approaches to eddy current nondestructive evaluation for stratified conductive structures. Journal of Mechanical Science and Technology, 29, 4159-4165. https://doi.org/10.1007/s12206-015-0910-7
• [19] Theodoulidis, T. P., & Kriezis, E. E. (2006). Eddy Current Canonical Problems (with Applications to Nondestructive Evaluation).
• [20] Trembovetska, R., Halchenko, V., & Bazilo, C. (2022, June). Inverse Multi-parameter Identification of Plane Objects Electrophysical Parameters Profiles by Eddy-Current Method. In: International Conference on Smart Technologies in Urban Engineering. 202-212. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-20141-7_19
• [21] Dodd C. V., Deeds W. E. (1975). Calculation of magnetic fields from time-varying currents in the presence of conductors (No. ORNL-TM-4958). Oak Ridge National Lab, (ORNL), Oak Ridge, TN (United States).
• [22] Halchenko, V. Ya., Trembovetska, R. V., Bazilo, C. V., & Tychkova N. B. (2023). Computer simulation of the process of profiles measuring of objects electrophysical parameters by surface eddy current probes. In Lecture Notes on Data Engineering and Communications Technologies: Proceedings of ITEST 2022, 178, 411-424. Springer Cham. https://doi.org/10.1007/978-3-031-35467-0_25
• [23] Halchenko, V. Y., Trembovetska, R., Tychkov, V. (2021). Surrogate synthesis of frame eddy current probes with uniform sensitivity in the testing zone. Metrology and Measurement Systems, 28(3). 551-564 https://doi.org/10.24425/mms.2021.137128
• [24] Raschka, S., & Mirjalili, V. (2019). Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2. 3rd Edition, Packt publishing Ltd.
• [25] Li, X., Jia, J., Yang, D., & Gu, Y. (2024). An integration method of a hybrid genetic algorithm and the Levenberg-Marquardt algorithm for ultrasonic testing. Metrology and Measurement Systems, 31(1), 165-177. https://doi.org/10.24425/mms.2024.148536
• [26] Yang, X., Cui, Y., Jia, L., Sun, Z., Zhang, P., Zhao, J., & Wang, R. (2023). Parameter identification of PMSM based on dung beetle optimization algorithm. Archives of Electrical Engineering, 72(4). 1055-1072. https://doi.org/10.24425/aee.2023.147426
• [27] Halchenko, V. Y., Yakimov, A. N., & Ostapuschenko, D. L. (2010). Global optimum search of functions with using of multiagent swarm optimization hybrid with evolutional composition formation of population. Information Technology, 10, 9-16.
• [28] Wang, Q. (2012). Kernel principal component analysis and its applications in face recognition and active shape models. arXiv preprint arXiv:1207.3538. https://doi.org/10.48550/arXiv.1207.3538
• [29] Halchenko, V., Trembovetska, R., Tychkov, V. (2024). Application of Reduced Order Surrogate Models for Solving Inverse Problems by the Optimization Method with a priori Information Accumulation. In: Faure, E., et al. Information Technology for Education, Science, and Technics. ITEST 2024. Lecture Notes on Data Engineering and Communications Technologies, 222, 127-142. Springer, Cham. https://doi.org/10.1007/978-3-031-71804-5 _9
• [30] Teterko, A. Y., & Gutnik, V. I. (2010). The concept of constructing equipment for multi-parameter eddy current monitoring. Selection and processing of information: Interdepartmental Collection of Scientific Papers, 33(109), 9-14. http://dspace.nbuv.gov.ua/handle/123456789/16217
• [31] Teterko, A. Y., & Hutnyk, V. I. (2011). Construction of the inverse transformation function for eddy current multiparameter testing devices. Materials Science, 47, 386-392. https://doi.org/10.1007/s11003-011-9407-4
• [32] Teterko, A. Y., & Nazarchuk, Z. T. (2004). Selective Eddy Current Flaw Detection. Karpenko Physicomechanical Institute, Ukrainian Academy of Sciences, Lviv.
• [33] Halchenko, V., Trembovetska, R., Tychkov, V., & Tychkova, N. (2023). Construction of Quasi-DOE on Sobol’s Sequences with Better Uniformity 2D Projections. Applied Computer Systems, 28(1), 21-34. https://doi.org/10.2478/acss-2023-0003
• [34] Halchenko, V. Y., Trembovetska, R. V., & Tychkov, V. V. (2021). Surrogate synthesis of excitation systems for frame tangential eddy current probes. Archives of Electrical Engineering, 70(4), 743-757. https://doi.org/10.24425/aee.2021.138258
• [35] Kuznetsov B. I., Nikitina T. B., Bovdui I. V., Chunikhin K. V., Kolomiets V. V., Kobylianskyi B. B. (2024). Method for prediction and control by uncertain microsatellite magnetic cleanliness based on calculation and compensation magnetic field spatial harmonics. Electrical Engineering & Electromechanics, (1), 23-33. https://doi.org/10.20998/2074-272X.2024.1.04
• [36] Kuznetsov B. I., Kutsenko A. S., Nikitina T. B., Bovdui I. V., Chunikhin K. V., Voloshko O. V. (2024). Hybrid Active and Passive Cable Contour Shielding of Magnetic Fields of Double-Circuit Overhead Power Lines. Problemele Energeticii Regionale, 62(2), 14-27. https://doi.org/10.52254/1857-0070.2024.2-62.02 (in Russian)
• [37] Koshevoy, N. D., Muratov, V. V., Kirichenko, A. L., & Borisenko, S. A. (2021). Application of the “jumping frogs” algorithm for research and optimization of the technological process. Radio Electronics, Computer Science, Control, 1(1), 57-65. https://doi.org/10.15588/1607-3274-2021-1-6
• [38] Koshevoy, N. D., Kostenko, E. M., & Muratov, V. V. (2020). Application of the fish searñh method for optimization plans of the full factor experiment. Radio Electronics, Computer Science, Control, (2), 44-50. https://doi.org/10.15588/1607-3274-2020-2-5

Uwagi

This work was supported as scientific and research work of Cherkasy State Technological University (Project #0122U200836).