Evidence map›Paper›PMID 41867948›Full record

ArticleWelding in the world2026

Evaluation of signal disturbance and recovery in phased array ultrasonic inspection during welding.

Angelos Dimakos, Nina E Sweeney, Charalampos Loukas, Christopher D Thompson, Sam Serjeant, Charles N MacLeod, Ehsan Mohseni, David Lines, James Sibson

Abstract read
In one paragraph

Article in Welding in the world, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Angelos DimakosCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.ORCID 0009-0007-9531-2216
Nina E SweeneyCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
Charalampos LoukasCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
Christopher D ThompsonCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
Sam SerjeantCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
Charles N MacLeodCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
Ehsan MohseniCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
David LinesCentre for Ultrasonic Engineering (CUE), Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, G1 1XQ UK.
James SibsonBabcock International Group, Babcock Technology Centre, Unit 100B Bristol Business Park, Stoke Gifford, Bristol, BS16 1EJ UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lack of sidewall fusion (LOSWF) is a critical defect in arc welding that compromises structural integrity, especially in multi-pass welds where buried discontinuities require highly advanced volumetric imaging techniques for detection. Traditional non-destructive testing (NDT) methods are often unable to identify such defects until fabrication is complete, increasing rework rates and overall build time. This study presents a novel approach, combining in-process ultrasonic imaging with controlled experimentation to enable LOSWF detection capability during welding. An experimental setup is introduced in which a static phased array probe is positioned ahead of the welding torch, allowing B-scan acquisition in real-time, during welding. Characteristic signal loss is observed prior to sidewall fusion, followed by echo recovery upon solidification-providing a dynamic indicator of fusion status, with a distinct amplitude drop from 60 to 0%, highlighting the binary nature of the monitoring. To benchmark detection limits, artificial LOSWF flaws were introduced into single-layer welds and evaluated using a roller probe configuration. In addition, experiments were performed to analyze signal degradation and recovery due to thermal disturbance, captured through C-scan sidewall echo analysis. The results demonstrate that ultrasonic imaging deployed during welding can offer both predictive and confirmatory information about fusion quality. This integrated approach provides a foundation for automated, embedded weld inspection systems that can identify fusion defects earlier in the process chain.

Indexed as

Artificial defect sensitivityAutomated weldingIn-process weld inspectionLack of sidewall fusion (LOSWF)Ultrasonic imaging

Identifiers

PMID41867948
PMCPMC13004750

What OpenQuestion holds

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Registered trials

None linked

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.