Evidence map›Paper›PMID 41829588›Full record

ArticleSensors (Basel, Switzerland)2026

Magnetic Induction Sensing of Corrosion on Steel Pipes: Feasibility, Instrument Design and First Test Results.

Verena Schifano, Guy Marquis, Pierre-Daniel Matthey, Martin G Luling, Hamza K Bennani, Luigi Kassir, Maher Kassir

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
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

7 authors.

Verena SchifanoInstitut Terre et Environnement de Strasbourg, UMR 7063 CNRS/Université de Strasbourg/ENGEES, 67084 Strasbourg, France.
Guy MarquisInstitut Terre et Environnement de Strasbourg, UMR 7063 CNRS/Université de Strasbourg/ENGEES, 67084 Strasbourg, France.ORCID 0000-0001-8971-6846
Pierre-Daniel MattheyInstitut Terre et Environnement de Strasbourg, UMR 7063 CNRS/Université de Strasbourg/ENGEES, 67084 Strasbourg, France.
Martin G LulingLulingTech SAS, 75019 Paris, France.ORCID 0000-0001-6136-5431
Hamza K BennaniSkipper NDT, 75001 Paris, France.
Luigi KassirSkipper NDT, 75001 Paris, France.
Maher KassirSkipper NDT, 75001 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Underground steel pipes are an essential component of the water and energy supply chains, and assessing their damage with standard techniques implies a temporary interruption in their use, often at a high cost to the operators. Evaluating the damage outside of the pipe would minimize these interruptions. In this work, we propose a new approach to investigating corrosion by taking advantage of the reduction in the steel's magnetic permeability resulting from it. To enhance these variations, the pipe is excited by a static magnetic field produced by a rectangular loop, inducing magnetization in the pipe that will be weaker where corrosion is present. The secondary magnetic fields produced by this magnetization are measured using an array of triaxial magnetic sensors. A desktop study using finite-element modelling confirmed the feasibility of the approach and informed the design of a first prototype. Scans of test pipes over a custom measurement bench show that corroded zones, as well as welding joints, generate significant anomalies with a strong signal-to-noise ratio, easily identified using simple signal processing techniques. These results confirm the viability of this non-invasive magnetostatic methodology.

Indexed as

corrosionmagnetic inductionnon-invasive techniques

Identifiers

PMID41829588
PMCPMC12987170

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.