ArticleScientific reports2026
Reducing noise levels in eddy current measurements using self-differential probes of the substrate conductivity under a layer of conductive coating in moved objects.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Eddy Current Classification of Sheet Ferromagnetic Materials Based on Material Property Profiles.Sensors (Basel, Switzerland) · 2026Article
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3 authors.
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Abstract
In the research, the method of reducing the levels of all noises caused by uncontrollable interfering factors has been generalized and extended to surface eddy current conductivity meters of the substrate under a layer of non-ferromagnetic metal coating. The method is applied at the probe design stage as a result of Taguchi's optimization search for a combination of ECP parameters that reduces the influence of noise factors. The designs of self-differential UECPs were analyzed. Dynamic measurements of substrate conductivity were considered. Variants of TO structures with non-magnetic and weakly magnetic substrates were investigated, i.e., eddy current conductivity measurements were extended to objects with weakly magnetic substrates. As a result of confirmatory experiments, the effectiveness of the obtained optimal combinations of parameters for both variants of TO structures was proven. The option with rectangular coils was selected as the one with the maximum SNR among the optimized alternative designs of the ECP. The variance analysis established the ranks of the influence of the measuring parameters on the SNR. The statistical significance of the analyzed parameters was determined. The Monte Carlo numerical-experimental method demonstrated the advantages of optimal designs, which are characterized by lower signal variability under the influence of noise factors.
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