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Journal articles on the topic 'Dynamic Preisach model'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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1

Sunny, Mohammed R., and Rakesh K. Kapania. "Modified Dynamic Preisach Model for Hysteresis." AIAA Journal 48, no. 7 (2010): 1523–30. http://dx.doi.org/10.2514/1.j050189.

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2

Kuczmann, Miklós. "Dynamic extension of vector Preisach model." Physica B: Condensed Matter 549 (November 2018): 47–52. http://dx.doi.org/10.1016/j.physb.2017.09.068.

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3

LU, M., P. J. LEONARD, P. MARKETOS, T. MEYDAN, and A. J. MOSES. "A SIMPLE DYNAMIC PREISACH HYSTERESIS MODEL FOR FeSi MATERIALS." International Journal of Modern Physics B 17, no. 11 (2003): 2325–31. http://dx.doi.org/10.1142/s0217979203018272.

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Dynamic hysteresis property is a common phenomenon in FeSi materials under time-varied applied field. This paper presented a dynamic hysteresis model based on Preisach scheme. The rectangular-shaped elementary hysteresis operator with two states in classical Preisach model is replaced by a non-rectangular shaped one with multiple states. The output of each state is calculated by a cosine function. The proposed dynamic hysteresis model is experimently tested by comparing the simulated hysteresis loops to experimental ones. The model can be used to describe the dynamic hysteresis in FeSi materia

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4

Yu, Y., Z. Xiao, N. G. Naganathan, and R. V. Dukkipati. "Dynamic Preisach modelling of hysteresis for the piezoceramic actuator system." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 215, no. 5 (2001): 511–21. http://dx.doi.org/10.1243/0954406011520913.

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A rate-dependent hysteresis property is a common phenomenon in various hysteretic systems including the piezoceramic material system. The dynamic Preisach model is needed to describe the rate-dependent hysteresis. This paper proposes a new dynamic Preisach model by introducing the dependence of the Preisach function on the input variation rate. An input variation rate function was introduced to adjust the relationship of hysteresis loop to the input variation rate for different hysteresis systems. A detailed numerical implementation procedure is also presented. Experiments were conducted to st

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5

Bernard, Y., E. Mendes, and F. Bouillault. "Dynamic hysteresis modeling based on Preisach model." IEEE Transactions on Magnetics 38, no. 2 (2002): 885–88. http://dx.doi.org/10.1109/20.996228.

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6

Grech, Christian, Marco Buzio, Mariano Pentella, and Nicholas Sammut. "Dynamic Ferromagnetic Hysteresis Modelling Using a Preisach-Recurrent Neural Network Model." Materials 13, no. 11 (2020): 2561. http://dx.doi.org/10.3390/ma13112561.

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In this work, a Preisach-recurrent neural network model is proposed to predict the dynamic hysteresis in ARMCO pure iron, an important soft magnetic material in particle accelerator magnets. A recurrent neural network coupled with Preisach play operators is proposed, along with a novel validation method for the identification of the model’s parameters. The proposed model is found to predict the magnetic flux density of ARMCO pure iron with a Normalised Root Mean Square Error (NRMSE) better than 0.7%, when trained with just six different hysteresis loops. The model is evaluated using ramp-rates

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7

Hussain, Sajid, and David Lowther. "The prediction of iron losses under PWM excitation using the classical Preisach model." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 35, no. 6 (2016): 1996–2006. http://dx.doi.org/10.1108/compel-03-2016-0126.

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Purpose The losses incurred in ferromagnetic materials under PWM excitations must be predicted accurately to optimize the design of modern electrical machines. The purpose of this paper is to employ mathematical hysteresis models (i.e. classical Preisach model) to predict iron losses in electrical steels under PWM excitation without compromising the computational complexity of the model. Design/methodology/approach In this paper, a novel approach based on the dynamic inverse Preisach model is proposed to model the iron losses. The PWM magnetic flux density waveform is decomposed into its harmo

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8

Bertotti, G. "Dynamic generalization of the scalar Preisach model of hysteresis." IEEE Transactions on Magnetics 28, no. 5 (1992): 2599–601. http://dx.doi.org/10.1109/20.179569.

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9

Kuczmann, Miklós. "Dynamic Preisach model identification applying FEM and measured BH curve." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, no. 6 (2014): 2043–52. http://dx.doi.org/10.1108/compel-11-2013-0368.

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Purpose – The purpose of this paper is to develop a viscous-type frequency dependent scalar Preisach hysteresis model and to identify the model using measured data and nonlinear numerical field analysis. The hysteresis model must be fast and well applicable in electromagnetic field simulations. Design/methodology/approach – Iron parts of electrical machines are made of non-oriented isotropic ferromagnetic materials. The finite element method (FEM) is usually applied in the numerical field analysis and design of this equipment. The scalar Preisach hysteresis model has been implemented for the s

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10

Rocca, G. La, V. Franzitta, Alessia Viola, and Marco Trapanese. "Dynamic Preisach Hysteresis Model for Magnetostrictive Materials for Energy Application." Applied Mechanics and Materials 432 (September 2013): 72–77. http://dx.doi.org/10.4028/www.scientific.net/amm.432.72.

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In this paper the magnetostrictive material considered is Terfenol-D. Its hysteresis is modeled by applying the DPM whose identification procedure is performed by using a neural network procedure previously publised [. The neural network used is a multiplayer perceptron trained with the Levenberg-Marquadt training algorithm. This allows to obtain the Preisach distribution function, without any special conditioning of the measured data, owing to the filtering capabilities of the neural network interpolators. The model is able to reconstruct both the magnetization relation and the Field-strain r

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11

Testa, Luigi, and Marco Trapanese. "Magnetic stochastic resonance in systems described by dynamic Preisach model." Physica B: Condensed Matter 403, no. 2-3 (2008): 486–90. http://dx.doi.org/10.1016/j.physb.2007.08.081.

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12

Trapanese, Marco. "Identification of parameters of dynamic Preisach model by neural networks." Journal of Applied Physics 103, no. 7 (2008): 07D929. http://dx.doi.org/10.1063/1.2836736.

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13

Dupre, L. R., G. Bertotti, and J. A. A. Melkebeek. "Dynamic Preisach model and energy dissipation in soft magnetic materials." IEEE Transactions on Magnetics 34, no. 4 (1998): 1168–70. http://dx.doi.org/10.1109/20.706433.

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14

Andrei, P., Al Stancu, and O. Caltun. "Differential Preisach model for the description of dynamic magnetization processes." Journal of Applied Physics 83, no. 11 (1998): 6359–61. http://dx.doi.org/10.1063/1.367688.

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15

Philips, D. A., L. R. Dupre, and J. A. A. Melkebeek. "Magneto-dynamic field computation using a rate-dependent Preisach model." IEEE Transactions on Magnetics 30, no. 6 (1994): 4377–79. http://dx.doi.org/10.1109/20.334091.

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16

Kung, Ying-Shieh, and Rong-Fong Fung. "Precision Control of a Piezoceramic Actuator Using Neural Networks." Journal of Dynamic Systems, Measurement, and Control 126, no. 1 (2004): 235–38. http://dx.doi.org/10.1115/1.1651535.

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In this paper, a control method combining the feedforward and feedback controllers is proposed to precisely control the dynamic performance of the piezoceramic actuator (PA). In the feedforward controller design, the hysteresis nonlinearity of the PA is modeled by using Preisach model first. Then a database of switching input/output values and a neural networks architecture treated as the inverse function of Preisach model are utilized in the feedforward controller. In the feedback controller design, a PI controller is used to regulate the output error. Finally, some experimental results are v

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17

Laure-Line, R., W. Thierry, K. Afef, and C. Jean-Louis. "Determination of the parameter k of the generalized dynamic Preisach model." IEEE Transactions on Magnetics 32, no. 3 (1996): 1124–27. http://dx.doi.org/10.1109/20.497440.

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18

Sunny, Mohammed R., and Rakesh K. Kapania. "Artificial-Neural-Network-Based Identification of a Modified Dynamic Preisach Model." International Journal for Computational Methods in Engineering Science and Mechanics 15, no. 1 (2013): 45–53. http://dx.doi.org/10.1080/15502287.2013.834001.

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19

Ni, Y. Q., Z. G. Ying, and J. M. Ko. "Random Response Analysis of Preisach Hysteretic Systems With Symmetric Weight Distribution." Journal of Applied Mechanics 69, no. 2 (2000): 171–78. http://dx.doi.org/10.1115/1.1428333.

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The present study is intended to develop a new method for analyzing nonlinear stochastic dynamic response of the Preisach hysteretic systems based on covariance and switching probability analysis of a nonlocal memory hysteretic constitutive model. A nonlinear algebraic covariance equation is formulated for the single-degree-of-freedom Preisach hysteretic system subjected to stationary Gaussian white noise excitation, from which the stationary mean square response of the system is obtained. The correlation coefficients of hysteretic restoring force with response in the covariance equation are e

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20

Dupré, L., G. Bertotti, V. Basso, F. Fiorillo, and J. Melkebeek. "Generalisation of the dynamic Preisach model toward grain oriented Fe–Si alloys." Physica B: Condensed Matter 275, no. 1-3 (2000): 202–6. http://dx.doi.org/10.1016/s0921-4526(99)00767-x.

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21

Basso, V., G. Bertotti, F. Fiorillo, and M. Pasquale. "Dynamic Preisach model interpretation of power losses in rapidly quenched 6.5% SiFe." IEEE Transactions on Magnetics 30, no. 6 (1994): 4893–95. http://dx.doi.org/10.1109/20.334257.

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22

Sarker, Pejush Chandra, Youguang Guo, Hai Yan Lu, and Jian Guo Zhu. "A generalized inverse Preisach dynamic hysteresis model of Fe-based amorphous magnetic materials." Journal of Magnetism and Magnetic Materials 514 (November 2020): 167290. http://dx.doi.org/10.1016/j.jmmm.2020.167290.

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23

Beatrice, C., M. Pasquale, and G. Bertotti. "Prediction of magnetic hysteresis in FeCoB amorphous materials using the dynamic Preisach model." IEEE Transactions on Magnetics 33, no. 5 (1997): 3772–74. http://dx.doi.org/10.1109/20.619567.

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24

Salvini, A., F. R. Fulginei, and G. Pucacco. "Generalization of the static preisach model for dynamic hysteresis by a genetic approach." IEEE Transactions on Magnetics 39, no. 3 (2003): 1353–56. http://dx.doi.org/10.1109/tmag.2003.810538.

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25

Ivanyi, Amalia, Peter Ivanyi, Miklos M. Ivanyi, and Miklos Ivanyi. "A Periodical Loaded Dynamical System." Materials Science Forum 721 (June 2012): 301–6. http://dx.doi.org/10.4028/www.scientific.net/msf.721.301.

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In the paper a Preisach hysteresis model is applied to determine the dynamic behavior of a steel column with a mass on the top and loaded by periodically alternating force. The column is considered as a completely rigid element, while the fixed end of the column is modeled with a rotational spring with hysteresis characteristic. In the solution of the non-linear dynamical equation of the motion the fix-point technique is inserted to the time marching iteration. The cycling time of the force is changing. The results are plotted in figures.

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26

Dang, Xuanju. "STUDY ON SIMILAR DIAGNAL DYNAMIC NEURAL NETWORK HYSTERESIS MODEL FOR PIEZOCERAMIC ACTUATOR BASED ON PREISACH MODEL." Chinese Journal of Mechanical Engineering 41, no. 04 (2005): 7. http://dx.doi.org/10.3901/jme.2005.04.007.

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27

Palumbo, Stefano, Mario Chiampi, Oriano Bottauscio, and Mauro Zucca. "Dynamic Simulation of a Fe-Ga Energy Harvester Prototype Through a Preisach-Type Hysteresis Model." Materials 12, no. 20 (2019): 3384. http://dx.doi.org/10.3390/ma12203384.

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This paper presents the modeling of an Fe–Ga energy harvester prototype, within a large range of values of operating parameters (mechanical preload, amplitude and frequency of dynamic load, electric load resistance). The simulations, based on a hysteretic Preisach-type model, employ a voltage-driven finite element formulation using the fixed-point technique, to handle the material nonlinearities. Due to the magneto–mechanical characteristics of Fe–Ga, a preliminary tuning must be performed for each preload to individualize the fixed point constant, to ensure a good convergence of the method. T

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28

ZHU, Yuchuan. "Dynamic Preisach Model in Giant Magnetostrictive Actuator Based on Hyperbolic Tangent Function Hysteresis Operators." Journal of Mechanical Engineering 50, no. 6 (2014): 165. http://dx.doi.org/10.3901/jme.2014.06.165.

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29

Vrijsen, N. H., J. W. Jansen, and E. A. Lomonova. "Force Prediction Including Hysteresis Effects in a Short-Stroke Reluctance Actuator Using a3d-FEM and the Preisach Model." Applied Mechanics and Materials 416-417 (September 2013): 187–94. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.187.

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Magnetic hysteresis effects, present in the force of an E-core reluctance actuator, are examined by simulations and measurements. Simulations have been performed with a 3d finite element method (3d-FEM) and a Preisach model, which is extended with a dynamic magnetic equivalent circuit (MEC) model. Both simulation methods are first examined on the prediction of the magnetic flux density in a closed-and open toroid for dc-and ac excitations. Finally, both methods are used to predict the force of the E-core reluctance actuator, which is compared to ac force measurementsperformed with a piezoelect

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30

Andrei, Petru, Ovidiu Caltun, and Alexandru Stancu. "Rate dependence of first-order reversal curves by using a dynamic Preisach model of hysteresis." Physica B: Condensed Matter 372, no. 1-2 (2006): 265–68. http://dx.doi.org/10.1016/j.physb.2005.10.063.

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31

Boudjema, M., I. B. Santos, K. R. McCall, R. A. Guyer, and G. N. Boitnott. "Linear and nonlinear modulus surfaces in stress space, from stress-strain measurements on Berea sandstone." Nonlinear Processes in Geophysics 10, no. 6 (2003): 589–97. http://dx.doi.org/10.5194/npg-10-589-2003.

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Abstract. The elastic response of many rocks to quasistatic stress changes is highly nonlinear and hysteretic, displaying discrete memory. Rocks also display unusual nonlinear response to dynamic stress changes. A model to describe the elastic behavior of rocks and other consolidated materials is called the Preisach-Mayergoyz (PM) space model. In contrast to the traditional analytic approach to stress-strain, the PM space picture establishes a relationship between the quasistatic data and a number density of hysteretic mesoscopic elastic elements in the rock. The number density allows us to ma

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32

Pasquale, M., and G. Bertotti. "Application of the dynamic Preisach model to the simulation of circuits coupled by soft magnetic cores." IEEE Transactions on Magnetics 32, no. 5 (1996): 4231–33. http://dx.doi.org/10.1109/20.539343.

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33

Ruderman, Michael, and Torsten Bertram. "Identification of Soft Magnetic B-H Characteristics Using Discrete Dynamic Preisach Model and Single Measured Hysteresis Loop." IEEE Transactions on Magnetics 48, no. 4 (2012): 1281–84. http://dx.doi.org/10.1109/tmag.2011.2172931.

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34

Kim, Hyeong-Seop, Ji-Hoon Han, Dong-Jin Choi, and Sun-Ki Hong. "A Study of Dynamic Characteristic Analysis for Hysteresis Motor Using Permeability and Load Angle by Inverse Preisach Model." Transactions of The Korean Institute of Electrical Engineers 68, no. 2 (2019): 262–68. http://dx.doi.org/10.5370/kiee.2019.68.2.262.

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35

Shunli Xiao and Yangmin Li. "Modeling and High Dynamic Compensating the Rate-Dependent Hysteresis of Piezoelectric Actuators via a Novel Modified Inverse Preisach Model." IEEE Transactions on Control Systems Technology 21, no. 5 (2013): 1549–57. http://dx.doi.org/10.1109/tcst.2012.2206029.

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36

Mayergoyz, I. D. "Dynamic Preisach models of hysteresis." IEEE Transactions on Magnetics 24, no. 6 (1988): 2925–27. http://dx.doi.org/10.1109/20.92290.

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37

Zirka, S. E., Y. I. Moroz, P. Marketos, and A. J. Moses. "Properties of dynamic Preisach models." Physica B: Condensed Matter 343, no. 1-4 (2004): 85–89. http://dx.doi.org/10.1016/j.physb.2003.08.037.

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38

Torre, E. D. "Dynamics in the Preisach accommodation model." IEEE Transactions on Magnetics 31, no. 6 (1995): 3799–801. http://dx.doi.org/10.1109/20.489776.

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39

Mayergoyz, I. D. "Dynamic vector Preisach models of hysteresis." Journal of Applied Physics 69, no. 8 (1991): 4829–31. http://dx.doi.org/10.1063/1.348246.

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40

Feng, Jianbo, Sizhong Chen, Zhiquan Qi, Jiaming Zhong, and Zheng Liu. "Electromagnetic Hysteresis Based Dynamics Model of an Electromagnetically Controlled Torque Coupling." Processes 7, no. 9 (2019): 557. http://dx.doi.org/10.3390/pr7090557.

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This paper proposes a novel computationally efficient, easy-to-implement electromagnetic hysteresis based dynamics model of a kind of intelligent electromagnetic torque controlled coupling (EMTC), which, with drag torque under consideration, first models the electromagnetic hysteresis existing in the primary clutch with the classical Preisach model, and then models the transferred torques in the three friction elements of the center coupling in the slipping and locked modes, respectively. The performance of the model is verified by simulation and experiment jointly, which lays the basis for th

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41

Zhang, B., B. Gupta, B. Ducharne, G. Sebald, and T. Uchimoto. "Preisach’s Model Extended With Dynamic Fractional Derivation Contribution." IEEE Transactions on Magnetics 54, no. 3 (2018): 1–4. http://dx.doi.org/10.1109/tmag.2017.2759421.

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42

Bermúdez, A., D. Gómez, and P. Venegas. "Mathematical analysis and numerical solution of models with dynamic Preisach hysteresis." Journal of Computational and Applied Mathematics 367 (March 2020): 112452. http://dx.doi.org/10.1016/j.cam.2019.112452.

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43

Wang, Dan, Linxiang Wang, and Roderick V. N. Melnik. "A Preisach-type model based on differential operators for rate-dependent hysteretic dynamics." Physica B: Condensed Matter 470-471 (August 2015): 102–6. http://dx.doi.org/10.1016/j.physb.2015.04.040.

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44

Liu, Yang, Xiasheng Guo, Zhao Da, Dong Zhang, and Xiufen Gong. "Imaging Cracks in Bones Using Acoustic Nonlinearity: A Simulation Study." Acta Acustica united with Acustica 97, no. 5 (2011): 728–33. http://dx.doi.org/10.3813/aaa.918452.

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This article proposes an acoustic nonlinear approach combined with the time reversal technique to image cracks in long bones. In this method, the scattered ultrasound generated from the crack is recorded, and the third harmonic nonlinear component of the ultrasonic signal is used to reconstruct an image of the crack by the time reversal process. Numerical simulations are performed to examine the validity of this approach. The fatigue long bone is modeled as a hollow cylinder with a crack of 1, 0.1, and 0.225 mm in axial, radial and circumferential directions respectively. A broadband 500 kHz u

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45

Royston, T. J. "Leveraging the Equivalence of Hysteresis Models From Different Fields for Analysis and Numerical Simulation of Jointed Structures." Journal of Computational and Nonlinear Dynamics 3, no. 3 (2008). http://dx.doi.org/10.1115/1.2908348.

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An important problem that spans across many types of systems (e.g., mechanical and biological) is how to model the dynamics of joints or interfaces in built-up structures in such a way that the complex dynamic and energy-dissipative behavior that depends on microscale phenomena at the joint/interface is accurately captured, yet in a framework that is amenable to efficient computational analyses of the larger macroscale system of which the joint or interface is a (spatially) small part. Simulating joint behavior in finite element analysis by meshing the joint regions finely enough to capture re

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46

Liu, Shih-Tang, Jia-Yush Yen, and Fu-Cheng Wang. "Compensation for the Residual Error of the Voltage Drive of the Charge Control of a Piezoelectric Actuator." Journal of Dynamic Systems, Measurement, and Control 140, no. 7 (2018). http://dx.doi.org/10.1115/1.4038636.

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One very effective approach to suppress hysteresis from the piezoelectric actuator is to use the charge control across the associated capacitance. The charge driver often uses an additional capacitor connected to the piezo-actuator in series for the charge sense feedback control. When this charge sense is used with a voltage drive for the charge control, the applied voltage will include two parts. The one is the voltage drop across the useful electro-mechanical part and effectively converted to the driving force, whereas the other part indicates the equivalent voltage drop due to the hysteresi

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47

Kopfová, Jana, Petra Nábělková, Dmitrii Rachinskii, and Samiha C. Rouf. "Dynamics of SIR model with vaccination and heterogeneous behavioral response of individuals modeled by the Preisach operator." Journal of Mathematical Biology 83, no. 2 (2021). http://dx.doi.org/10.1007/s00285-021-01629-8.

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