Reducing noise levels in eddy current measurements using self-differential probes of the substrate conductivity under a layer of conductive coating in moved objects

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-03-23
DOI
https://doi.org/10.1038/s41598-026-42808-1
Primary Topic
Non-Destructive Testing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reducing noise levels in eddy current measurements using self-differential probes of the substrate conductivity under a layer of conductive coating in moved objects

Volodymyr Tychkov, Volodymyr Ya. Halchenko, Ruslana Trembovetska
Scientific Reports
Non-Destructive Testing Techniques
article

Reducing noise levels in eddy current measurements using self-differential probes of the substrate conductivity under a layer of conductive coating in moved objects

Volodymyr Tychkov, Volodymyr Ya. Halchenko, Ruslana Trembovetska
article en

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.

Scientific Reports
Cherkasy State Technological University (UA)
Affordable and clean energy
Openalex Percentile: Top 12%
Non-Destructive Testing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.