Evidence map›Paper›PMID 41600332›Full record

ArticleSensors (Basel, Switzerland)2026

High-Resolution Spatiotemporal-Coded Differential Eddy-Current Array Probe for Defect Detection in Metal Substrates.

Qi Ouyang, Yuke Meng, Lun Huang, Yun Li

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qi OuyangSchool of Automation, Chongqing University, Chongqing 400044, China.
Yuke MengSchool of Automation, Chongqing University, Chongqing 400044, China.ORCID 0009-0007-1054-1539
Lun HuangSouthwest Institute of Technology and Engineering, China South Industries Group, Chongqing 400039, China.
Yun LiSchool of Automation, Chongqing University, Chongqing 400044, China.

Funding

Cooperative Fund Project of the Southwest Institute of Technology and Engineering, China South Industries Group Corporation HDHDW5923C010102
6 · The paper itself

Abstract

To address the problems of weak geometric features, low signal response amplitude, and insufficient spatial resolvability of near-surface defects in metal substrates, a high-resolution spatiotemporal-coded eddy-current array probe is proposed. The probe adopts an array topology with time-multiplexed excitation and adjacent differential reception, achieving a balance between high common-mode rejection ratio and high-density spatial sampling. First, a theoretical electromagnetic coupling model between the probe and the metal substrate is established, and finite-element simulations are conducted to investigate the evolution of the skin effect, eddy-current density distribution, and differential impedance response over an excitation frequency range of 1-10 MHz. Subsequently, a 64-channel M-DECA probe and an experimental testing platform are developed, and frequency-sweeping experiments are carried out under different excitation conditions. Experimental results indicate that, under a 50 kHz excitation frequency, the array eddy-current response achieves an optimal trade-off between signal amplitude and spatial geometric consistency. Furthermore, based on the pixel-to-physical coordinate mapping relationship, the lateral equivalent diameters of near-surface defects with different characteristic scales are quantitatively characterized, with relative errors of 6.35%, 4.29%, 3.98%, 3.50%, and 5.80%, respectively. Regression-based quantitative analysis reveals a power-law relationship between defect area and the amplitude of the differential eddy-current array response, with a coefficient of determination R2=0.9034 for the bipolar peak-to-peak feature. The proposed M-DECA probe enables high-resolution imaging and quantitative characterization of near-surface defects in metal substrates, providing an effective solution for electromagnetic detection of near-surface, low-contrast defects.

Indexed as

defect detectiondifferential eddy-current array probehigh-resolution imagingquantitative evaluationspatiotemporal coding

Identifiers

PMID41600332
PMCPMC12845729

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