Evidence map›Paper›PMID 41682428›Full record

ArticleSensors (Basel, Switzerland)2026

Digital Image Correlation-Based Bolt Preload Monitoring.

Linsheng Huo, Liukun Zhao, Aocheng Hu, Fanwei Meng, Hongnan 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
–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

5 authors.

Linsheng HuoState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.ORCID 0000-0002-3044-2630
Liukun ZhaoState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.
Aocheng HuState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.
Fanwei MengState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.
Hongnan LiState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.

Funding

National Natural Science Foundation of China 51778111
6 · The paper itself

Abstract

Bolt connections are widely used in engineering structures but are susceptible to loosening during operation, which can result in significant safety concerns. Consequently, reliable bolt-loosening detection is of paramount importance. Conventional detection methodologies frequently exhibit deficiencies, including reduced efficiency, constrained accuracy, and the requirement for contact sensors. To overcome these limitations, this study proposes a novel non-contact approach for bolt preload monitoring based on Digital Image Correlation (DIC). In this method, an industrial camera captures speckle images of the bolt head before and after deformation, thereby enabling measurement of the surface strain. The DIC technique is employed to calculate the strain field on the bolt head surface, which exhibits a linear relationship with the bolt preload. The proposed method utilizes strain field tracking to facilitate effective and precise monitoring of bolt preload. Experimental results demonstrate that the method provides a precise, efficient, and user-friendly solution for bolt preload monitoring, showing great potential for applications in structural health monitoring.

Indexed as

bolt looseness monitoringbolt preloaddigital image correlationstructural health monitoring

Identifiers

PMID41682428
PMCPMC12899918

What OpenQuestion holds

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LicenceCC BY
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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.