2021
DOI: 10.1109/temc.2020.3020049
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Identifying Interference From Multiple Noise Sources Using Only Magnetic Near Fields

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Cited by 9 publications
(2 citation statements)
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“…Moreover, the usage of FDM inherits its shortcomings in terms of numerical errors [21]. The source reconstruction algorithm in [22] based on the Finite Element Method (FEM) has also been used to predict the far field in the context of EMI and identifying the location of interference from multiple source [23] based on the estimation of s-parameters. The success of these methods is based on the phase measurement where recently promising low cost alternatives are proposed [24], [25].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the usage of FDM inherits its shortcomings in terms of numerical errors [21]. The source reconstruction algorithm in [22] based on the Finite Element Method (FEM) has also been used to predict the far field in the context of EMI and identifying the location of interference from multiple source [23] based on the estimation of s-parameters. The success of these methods is based on the phase measurement where recently promising low cost alternatives are proposed [24], [25].…”
Section: Introductionmentioning
confidence: 99%
“…The SWE method is very efficient and accurate [2, 3], thus it could be iteratively applied using an optimisation algorithm or, alternatively, using an artificial intelligence process to identify the best tray settings and the best rack assembly that minimises the overall rack radiation. The work described in this paper investigates the possibility of applying the SWE method, differently from its typical application for far‐field (FF) reconstruction from near‐field (NF) measurements of antennas or large arrays [4–6], in order to have an alternative and more accurate way, with respect to other techniques [7, 8], to predict EMI radiation. The SWE technique is applied to the tangential electric field (E‐field) detected on a surface surrounding the tray under test to evaluate the spherical wave coefficients associated to each source [1–4].…”
Section: Introductionmentioning
confidence: 99%