A neural network approach for determination of Preisach model parameters under a sinusoidal induction at various frequencies

被引：6
|
作者：
Moussaoui, D
Bendjerad, A
Oussalah, M
Houassine, H
机构：
[1] UER Electrotech EMP, ENITA, Lab Electromagnet Sys, Algiers, Algeria
[2] Univ Birmingham, Sch Engn Elect Elect & Comp Engn, Birmingham B15 2TT, W Midlands, England
来源：
PHYSICA B-CONDENSED MATTER | 2006年 / 372卷 / 1-2期
关键词：
neural network; Preisach model; hysteresis; magnetic losses;
D O I：
10.1016/j.physb.2005.10.027
中图分类号：
O469 [凝聚态物理学];
学科分类号：
070205 ;
摘要：
In this paper, we present a neural network-based approach, which allows us to predict the hysteretic loop, whatever the value of the frequency and flux density. The approach makes use of the Preisach-hysteretic model (PM) which provides a mathematical model to the B(H) curve, while the neural enables us to identify and predict the behaviour of parameters that the PM needs. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：106 / 110
页数：5
相关论文
共 50 条
  • [1] Identification Parameters with Neural Network for Preisach Hysteresis Model
    Amir, Mounir
    Zergoug, Mourad
    Amrouche, Aissa
    ENGINEERING AND MANUFACTURING TECHNOLOGIES, 2014, 541-542 : 487 - 493
  • [2] Modeling of Memristors Under Sinusoidal Excitations with Various Frequencies
    Garda, Bartlomiej
    Galias, Zbigniew
    2018 25TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS (ICECS), 2018, : 545 - 548
  • [3] Neural-network-based model for dynamic hysteresis in the magnetostriction of electrical steel under sinusoidal induction
    Hilgert, Tom
    Vandevelde, Lieven
    Melkebeek, Jan
    IEEE TRANSACTIONS ON MAGNETICS, 2007, 43 (08) : 3462 - 3466
  • [4] Identification of parameters of dynamic Preisach model by neural networks
    Trapanese, Marco
    JOURNAL OF APPLIED PHYSICS, 2008, 103 (07)
  • [5] An improved neural network approach to the determination of aquifer parameters
    Lin, GF
    Chen, GR
    JOURNAL OF HYDROLOGY, 2006, 316 (1-4) : 281 - 289
  • [6] A NEURAL-NETWORK APPROACH TO THE DETERMINATION OF AQUIFER PARAMETERS
    AZIZ, ARA
    WONG, KFV
    GROUND WATER, 1992, 30 (02) : 164 - 166
  • [7] Determination of distribution functions and parameters for the Preisach hysteresis model
    Pruksanubal, P.
    Binner, A.
    Gonschorek, K. H.
    2006 17TH INTERNATIONAL ZURICH SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY, VOLS 1 AND 2, 2006, : 258 - +
  • [8] A simple neural network model for the determination of aquifer parameters
    Samani, N.
    Gohari-Moghadam, M.
    Safavi, A. A.
    JOURNAL OF HYDROLOGY, 2007, 340 (1-2) : 1 - 11
  • [9] Identification of the Parameters of Reduced Vector Preisach Model by Neural Networks
    Trapanese, Marco
    IEEE TRANSACTIONS ON MAGNETICS, 2008, 44 (11) : 3197 - 3200
  • [10] A MODEL OF A NEURAL NETWORK ACTIVITY UNDER THE INFLUENCE OF VARIOUS TRANSMITTERS
    FROLOV, AA
    ORLOVA, MP
    KOSHTOYANTS, OK
    MARKAROVA, MJ
    SHULGINA, GI
    ZHURNAL VYSSHEI NERVNOI DEYATELNOSTI IMENI I P PAVLOVA, 1982, 32 (02) : 310 - 318
12345