DocumentCode :
1755252
Title :
A Semianalytical Heuristic Approach for Prediction of Eut's Multiple Dipole Model by Reducing the Number of Heuristics
Author :
Kakarakis, Sarantis-Dimitrios J. ; Kapsalis, Nicolas C. ; Capsalis, Christos N.
Author_Institution :
Nat. Tech. Univ. of Athens, Athens, Greece
Volume :
57
Issue :
1
fYear :
2015
fDate :
Feb. 2015
Firstpage :
87
Lastpage :
92
Abstract :
A novel multiple dipole modeling (MDM) calculation scheme is proposed for prediction of the magnetic behavior of an equipment under test (EUT). The MDM calculation scheme is based on a semianalytical approach leading to less heuristics needed to be determined; thus, leading to a more efficient MDM determination. A genetic algorithm approach is adopted to minimize the root mean square error between the measured magnetic fields of the EUT and the MDM. To validate the proposed scheme and investigate its performance, numerous simulations have been employed. Simulation results regarding a mix of different EUT and the corresponding MDMs magnetic fields demonstrate the capability of the proposed scheme to optimally determine the MDMs and explore some topics about the measuring procedure of an EUT, depending on the distance and the number of the observation points. Furthermore, it is shown that the number of dipoles chosen to compose the MDM is of crucial importance.
Keywords :
genetic algorithms; magnetic fields; mean square error methods; EUT measuring procedure; EUT multiple-dipole model prediction; MDM calculation scheme; equipment-under-test; genetic algorithm approach; heuristic reduction; magnetic behavior prediction; magnetic field measurement; root mean square error minimization; semianalytical heuristic approach; Accuracy; Distortion measurement; Magnetic moments; Magnetostatics; Position measurement; Prediction algorithms; Predictive models; Genetic algorithms (GAs); magnetic dipole model (MDM); magnetic field measurements;
fLanguage :
English
Journal_Title :
Electromagnetic Compatibility, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9375
Type :
jour
DOI :
10.1109/TEMC.2014.2358712
Filename :
6912957
Link To Document :
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