Difficulty in identification of Preisach hysteresis model weighting function using first order reversal curves method in soft magnetic materials
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F17%3A00004317" target="_blank" >RIV/46747885:24220/17:00004317 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1016/j.amc.2017.05.017" target="_blank" >http://dx.doi.org/10.1016/j.amc.2017.05.017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.amc.2017.05.017" target="_blank" >10.1016/j.amc.2017.05.017</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Difficulty in identification of Preisach hysteresis model weighting function using first order reversal curves method in soft magnetic materials
Popis výsledku v původním jazyce
The Preisach model can be used for detailed analysis of devices based on ferromagnetic materials, if its parameter, its weighting function, is well-known. Usually the weighting function is approximated by analytical formula. The second approach is to determine it directly from experimental data. Most widely used method to obtain the weighting func- tion is the first order reversal curve method that is based on two partial derivatives of measured magnetization using a special excitation pattern beginning from deep material saturation. Since the derivative enhances the experimental error, a precision experiment is necessary. Furthermore, it is not easy to achieve the deep saturation with the required signal pattern. Therefore sophisticated data processing followed, in order to reduce ex- perimental errors before performing the numerical derivative. The paper concerns mea- surements errors caused by insufficient saturation and also problems of negative values of the weighting function, partially due to the noise. Irrespective of measurement errors, the agreement between model and experiment is good and fully acceptable in technical praxis.
Název v anglickém jazyce
Difficulty in identification of Preisach hysteresis model weighting function using first order reversal curves method in soft magnetic materials
Popis výsledku anglicky
The Preisach model can be used for detailed analysis of devices based on ferromagnetic materials, if its parameter, its weighting function, is well-known. Usually the weighting function is approximated by analytical formula. The second approach is to determine it directly from experimental data. Most widely used method to obtain the weighting func- tion is the first order reversal curve method that is based on two partial derivatives of measured magnetization using a special excitation pattern beginning from deep material saturation. Since the derivative enhances the experimental error, a precision experiment is necessary. Furthermore, it is not easy to achieve the deep saturation with the required signal pattern. Therefore sophisticated data processing followed, in order to reduce ex- perimental errors before performing the numerical derivative. The paper concerns mea- surements errors caused by insufficient saturation and also problems of negative values of the weighting function, partially due to the noise. Irrespective of measurement errors, the agreement between model and experiment is good and fully acceptable in technical praxis.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Applied Mathematics and Computation
ISSN
0096-3003
e-ISSN
—
Svazek periodika
319
Číslo periodika v rámci svazku
February
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
17
Strana od-do
469-485
Kód UT WoS článku
000415906200037
EID výsledku v databázi Scopus
2-s2.0-85019479393