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Reliability and Efficiency of Differential Evolution Based Method of Determination of Jiles-Atherton Model Parameters for X30CR13 Corrosion Resisting Martensitic Steel

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Języki publikacji
EN
Abstrakty
EN
Paper presents new possibilities of Jiles-Atherton model of magnetic hysteresis parameters determination. The main problem connected with this model is the fact that its parameters have to be determined during the optimization process. However, due to the local minima on the target function, the gradient optimization methods are not effective, whereas evolutionary strategies, such as (μ+λ) strategy, are very time consuming. Results of calculation presented in the paper indicate that differential strategies create possibility of reliable and fast determination of Jiles-Atherton model parameters. Paper also presents guidelines for practical determination of model’s parameters, which is very important from practical point of view.
Twórcy
  • Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
  • Institute of Metrology and Biomedical, Engineering Warsaw University of Technology, sw. A. Boboli 8, 02-525 Warsaw, Poland
autor
  • Industrial Research Institute for Automation and Measurements, Al. Jerozolimskie 202, 02-486 Warsaw, Poland
Bibliografia
  • [1] Jiles D.C., Thoelke J.B., Devine M.K., “Numerical determination of hysteresis parameters for the modeling of magnetic properties using the theory of ferromagnetic hysteresis”, IEEE Transactions on Magnetics, vol. 28, no: 1, 1992, 27–35.DOI: 10.1109/20.119813.
  • [2] Jiles D. C., Atherton D., “Theory of ferromagnetic hysteresis”, Journal of Magnetism and Magnetic Materials, vol. 61, no. 1–2, 1986, 48–60, DOI:10.1016/0304-8853(86)90066-1.
  • [3] Szewczyk R., “Validation of the Anhysteretic Magnetization Model for Soft Magnetic Materials with Perpendicular Anisotropy”, Materials, vol. 7, no. 7, 2014, 5109–5116. DOI:10.3390/ma7075109.
  • [4] Jiles D. C., Atherton D.L., “Theory of ferromagnetic hysteresis”, Journal of Applied Physics, vol. 55, no. 6, 1984, 2115–2120. DOI:10.1063/1.333582.
  • [5] Jiles D.C., Ramesh A., Shi Y., Fang X., “Application of the anisotropic extension of the theory of hysteresis to the magnetization curves of crystalline and textured magnetic materials”, IEEE Transactions on Magnetics, vol. 33, no. 5, 1997, 3961–3963. DOI: 10.1109/20.619629.
  • [6] Chwastek K., Szczygłowski J., “Estimation methods for the Jiles-Atherton model parameters – a review” Przegląd Elektrotechniczny, vol. 84, no. 12, 2008, 145–147.
  • [7] Szewczyk R., “Modelling of the Magnetic Characteristics of Isotropic and Anisotropic Materials for Sensor Applications”, ACTA Physica Polonica A, vol. 113, no. 1, 2008, 67–70.
  • [8] Atkinson K., “An Introduction to Numerical Analysis”, New York, John Wiley & Sons, 1989.
  • [9] Shampine L. F., “Vectorized Adaptive Quadrature in MATLAB”, Journal of Computational and Applied Mathematics, vol. 211, no. 2, 2008, 131–140. DOI: 10.1016/j.cam.2006.11.021.
  • [10] Jackiewicz D., Szewczyk R., Salach J., Bienkowski A., Kachniarz M., “Influence of Stresses on Magnetic B-H Characteristics of X30Cr13 Corrosion Resisting Martensitic Steel”, Recent Advances in Automation, Robotics and Measuring Techniques Advances in Intelligent Systems and Computing, vol. 267, 2014, 607–614. DOI:10.1007/978-3-319-05353-0_57.
  • [11] Kachniarz M., Jackiewicz D., Nowicki M., Bieńkowski A., Szewczyk, Winiarski W., “Magnetoelastic Characteristics R. of Constructional Steel Materials”, Mechatronics – Ideas for Industrial Application, Advances in Intelligent Systems and Computing, vol. 317, 2015, 307–315. DOI: 10.1007/978-3-319-10990-9_28
  • [12] Baodong B., Jiayin W., Keqing Z., “Identification of the Jiles-Atherton model parameters using Simulated annealing method”. In: 2011 International Conference on Electrical Machines and Systems (ICEMS), 2011, 1–4. DOI: 10.1109/ICEMS.2011.6073612
  • [13] Teodorescu P., Stanescu N., Pandrea N., Optimizations, Wiley-IEEE Press, 2013.
  • [14] R. Fletcher, Practical methods of optimization, 2nd ed., John Wiley & Sons, 1987.
  • [15] Hestenes M., Stiefel E., “Methods of Conjugate Gradients for Solving Linear Systems”, Journal of Research of the National Bureau of Standards, vol. 49, no. 6, 1952, 409–436.
  • [16] H. G. Beyer, The Theory of Evolution Strategies, Natural Computing Series, Springer 2001. DOI: http://dx.doi.org/10.1007/978-3-662-04378-3.
  • [17] Rechenberg I., Evolutionsstrategie ‘94, Frommann-Holzboog Verlag, Stuttgart, 1994.
  • [18] Biedrzycki R., Szewczyk R., Švec P., Winiarski W., “Determination of Jiles-Atherton Model Parameters Using Differential Evolution”, Mechatronics – Ideas for Industrial Application,Advances in Intelligent Systems and Computing, vol. 317, 2015, 11–18. DOI: 10.1007/978-3-319-10990-9_2.
  • [19] Hansen N., Ostermeier A., “Completely derandomized self-adaptation in evolution strategies”, Journal Evolutionary Computation, vol. 9, no. 2, 2001, 159–195. DOI: 10.1162/106365601750190398.
  • [20] V. Feoktistov, “Differential Evolution”, Springer Optimization and Its Applications, vol. 5, Springer 2006.
  • [21] R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, 2013.
  • [22] Ardia D., Mullen K. M., Peterson B. G., Ulrich J., DEoptim: Differential Evolution in R, R Package Version, 2007, 1.3-0.
  • [23] Jackiewicz D., Salach J., Szewczyk R., Bienkowski A., “Application of Extended Jiles-Atherton Model for Modelling the Influence of Stresses on Magnetic Characteristics of the Construction Steel”, Acta Physica Polonica A, vol. 126.no. 1, 2014, 392–393. DOI:10.12693/APhysPolA.126.392.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-758c4adb-2143-482f-b95b-aa37e6ba2d60
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