Mathematical Modeling
Vol. 4 (2020), Issue 3, pg(s) 86-90

MATHEMATICAL MODELLING OF TECHNOLOGICAL PROCESSES AND SYSTEMS

Linear synthesis of frame eddy current probes with a planar excitation system

  • 1 Faculty of Electronic Technologies and Robotics – Cherkasy State Technological University, Ukraine

Abstract

A mathematical method of linear surrogate parametric synthesis of frame surface non-coaxial eddy current probes with a uniform eddy current density distribution in the testing object’s zone is proposed. The metamodel of a frame eddy current probe with a planar structure of the excitation system is constructed. Acceptable accuracy of the created metamodel is obtained by using the decomposition of the extremum search space and using associative neural networks. Examples of the synthesis of such excitation systems using modern metaheuristic stochastic algorithms for finding the global extremum are considered. The numerical results of the obtained solution and graphic illustrative material of the density distribution of the eddy currents on the surface in the testing object’s zone are given.

Keywords

References

  1. Rosado L.S., Gonzalez J.C., Santos T.G., Ramos P.M., Piedade M. Geometric optimization of a differential planar eddy currents probe for non-destructive testing. Sensors and Actuators A: Physical. - 2013. - V. 197. - P. 96-105. https://doi.org/10.1016/j.sna.2013.04.010
  2. Su Z., Efremov A., Safdarnejad M., Tamburrino A., Udpa L., Udpa S. Optimization of coil design for near uniform interrogating field generation / Z. AIP Conference Proceedings. - 2015. - V. 1650. - P. 405–413. https://doi.org/10.1063/1.4914636
  3. Su Z., Ye C., Tamburrino A., Udpa L., Udpa S. Optimization of coil design for eddy current testing of multi-layer structures. International Journal of Applied Electromagnetics and Mechanics. - 2016. – V. 52. - № 1-2. - Р. 315-322. https://doi.org/10.3233/JAE-162030
  4. Repelianto A.S., Kasai N., Sekino K., Matsunaga M. A Uniform Eddy Current Probe with a Double-Excitation Coil for Flaw Detection on Aluminium Plates. Metals. - 2019. - № 9. - Article № 1116. https://doi.org/10.3390/met9101116
  5. Liu Z., Yao J., He C., Li Z., Liu X., Wu B. Development of a bidirectional-excitation eddy-current sensor with magnetic shielding: Detection of subsurface defects in stainless steel. IEEE Sensors J. - 2018. - V. 18. - № 15. - Р. 6203-6216. https://doi.org/10.1109/JSEN.2018.2844957
  6. Halchenko V.Ya., Trembovetskaya R.V., Tychkov V.V. Surface eddy current probes: excitation systems of the optimal electromagnetic field (review). Devices and Methods of Measurements. 2020. № 1 (11). P. 42-52. https://doi.org/10.21122/2220-9506-2020-11-2-91-104
  7. Halchenko V.Ya., Trembovetska R.V., Tychkov V.V., Storchak A.V. Nonlinear surrogate synthesis of the surface circular eddy current probes. Przegląd elektrotechniczny. – 2019. - № 9. – P. 76-82. https://doi.org/10.15199/48.2019.09.15
  8. Trembovetska R.V., Halchenko V.Ya., Tychkov V.V. Optimal surrogate parametric synthesis of surface circular non-axial eddy current probes with uniform sensitivity in the testing zone / // Bulletin of the Kherson National Technical University. - 2019. – № 2(69). - Part 2. - P. 118-125. https://mkmm.org.ua/upload/%D0%92%D1%96%D1%81%D0 %BD%D0%B8%D0%BA%20%D0%A5%D0%9D%D0%A2% D0%A3%20%D1%87%D0%B0%D1%81%D1%82%D0%B8% D0%BD%D0%B0%202.pdf
  9. Halchenko V.Ya., Trembovetska R.V., Tychkov V.V. Linear synthesis of non-axial surface eddy current probes. International Journal “NDT Days”. - 2019. - Vol. 2. - Issue. 3. - P. 259-268. https://www.ndt.net/article/NDTDays2019/papers/JNDTD-v2- n3-a03.pdf
  10. Trembovetska R.V., Halchenko V.Y., Tychkov V.V. Multiparameter hybrid neural network metamodel of eddy current probes with volumetric structure of excitation system. International Scientific Journal «Mathematical Modeling». 2019. № 4 (3) P. 113-116. https://stumejournals.com/journals/mm/2019/4/113
  11. Itaya T., Ishida K., Kubota Y., Tanaka A., Takehira N. Visualization of Eddy Current Distributions for Arbitrarily Shaped Coils Parallel to a Moving Conductor Slab. Progress in Electromagnetics Research M. 2016. Vol. 47. Pp. 1-12. https://doi.org/10.2528/PIERM16011204
  12. Trembovetska R.V., Halchenko V.Ya., Tychkov V.V. Studying the computational resource demands of mathematical models for moving surface eddy current probes for synthesis problems. Eastern-European Journal of Enterprise Technologies. – 2018. - № 5/5 (95). - P. 39-46. https://doi.org/10.15587/1729-4061.2018.143309
  13. Halchenko V.Ya., Trembovetskaya R.V., Tychkov V.V. Development of excitation structure RBF-metamodels of moving concentric eddy current probe. Electrical Engineering & Electromechanics. - 2019. - No 1. - P. 28-38. https://doi.org/10.20998/2074-272X.2019.2.05
  14. Halchenko V.Ya., Trembovetska R.V., Tychkov V.V., Storchak A.V. The Construction of Effective Multidimensional Computer Designs of Experiments Based on a Quasi-random Additive Recursive Rd–sequence. Applied Computer Systems. 2020. Vol. 25, No. 1. Pp. 70-76. https://doi.org/10.2478/acss-2020-0009
  15. Halchenko V.Ya., Trembovetska R.V., Tychkov V.V., Storchak A.V. Methods for creating metamodels: state of the question. Bulletin of Vinnitsa Polytechnic Institute. - 2020. - No. 4 (151). - P. 74 - 88. https://doi.org/10.31649/1997-9266-2020-151-4-74-88
  16. Géron A. Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. 2nd Edition. O'Reilly Media, Inc. 2019. 856 p. ISBN-10: 1492032646.
  17. Halchenko V.Ya., Yakimov A.N. Population Metaheuristic Optimization Algorithms by a Particles Swarm: A Study Guide. Cherkasy. Publ. by Tretyakov A.N., 2015.160 p. ISBN 978-617-7318-06-3.

Article full text

Download PDF