TY - CHAP A1 - Seliger, Norbert A1 - Faltlhauser, Georg T1 - Active Expansion Sampling of Magnetic Near-Fields in Unbounded Regions T2 - Proceedings 26th IEEE Workshop on Signal and Power Integrity (IEEE SPI-2022) KW - Magnetic Near Field Scanning, Machine Learning, Active Expansion Sampling, Method of Moments Y1 - 2022 PB - IEEE ER - TY - JOUR A1 - Seliger, Norbert A1 - Faltlhauser, Georg T1 - Progressive Expansion Sampling of Quasi-Static Magnetic Fields in Unconfined Regions JF - IEEE Transactions on Components, Packaging and Manufacturing Technology N2 - We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits 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 identifies contours of given field limits in less than 3% of the reference measurement time. KW - Progressive Expansion Sampling KW - Near-Field Scanning KW - Machine Learning KW - Gaussian Process Classifier KW - MoM modeling Y1 - 2023 U6 - https://doi.org/10.1109/TCPMT.2023.3283285 ER - TY - CHAP A1 - Seliger, Norbert A1 - Faltlhauser, Georg T1 - Progressive Expansion Sampling of Quasi-Static Magnetic Fields for EMI Noise Detection and Equivalent Source Modeling T2 - Proceedings EMC Europe 2023 N2 - 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. KW - magnetic near field KW - Gaussian process classifier KW - EMI Y1 - 2023 PB - IEEE CY - Krakov ER -