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.
Author: | Norbert SeligerORCiD, Georg Faltlhauser |
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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 |