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Progressive Expansion Sampling of Quasi-Static Magnetic Fields for EMI Noise Detection and Equivalent Source Modeling

  • We introduce a quick and accurate quasi-static magnetic field scanning technique by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on a printed circuit board test structure. We prove allocation of multiple, separated regions with predefined tangential field strengths at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling detects contours of given field limits in less than 3% of the reference measurement time.

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Metadaten
Author:Norbert SeligerORCiD, Georg Faltlhauser
Parent Title (English):Proceedings EMC Europe 2023
Publisher:IEEE
Place of publication:Krakov
Document Type:Conference Proceeding
Language:English
Publication Year:2023
Tag:EMI; Gaussian process classifier; magnetic near field
Page Number:6
Peer reviewed:Nein
faculties / departments:Fakultät für Ingenieurwissenschaften
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 60 Technik / 600 Technik, Technologie