Evidence map›Paper›PMID 36992010›Full record

ArticleSensors (Basel, Switzerland)2023

Digital Fringe Projection-Based Clamping Force Estimation Algorithm for Railway Fasteners.

Zhengji Fan, Yingping Hong, Yunfeng Wang, Yanan Niu, Huixin Zhang, Chengqun Chu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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

6 authors.

Zhengji FanSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.ORCID 0000-0002-5673-1860
Yingping HongSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.ORCID 0000-0003-2575-7539
Yunfeng WangSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.
Yanan NiuSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.
Huixin ZhangSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.
Chengqun ChuSchool of Instrument and Electronics, North University of China, Taiyuan 030051, China.

Funding

Shanxi Province Colleges and Universities Science and Technology Innovation Project 2019L0539
6 · The paper itself

Abstract

The inspection of railway fasteners to assess their clamping force can be used to evaluate the looseness of the fasteners and improve railway safety. Although there are various methods for inspecting railway fasteners, there is still a need for non-contact, fast inspection without installing additional devices on fasteners. In this study, a system that uses digital fringe projection technology to measure the 3D topography of the fastener was developed. This system inspects the looseness through a series of algorithms, including point cloud denoising, coarse registration based on fast point feature histograms (FPFH) features, fine registration based on the iterative closest point (ICP) algorithm, specific region selection, kernel density estimation, and ridge regression. Unlike the previous inspection technology, which can only measure the geometric parameters of fasteners to characterize the tightness, this system can directly estimate the tightening torque and the bolt clamping force. Experiments on WJ-8 fasteners showed a root mean square error of 9.272 N·m and 1.94 kN for the tightening torque and clamping force, demonstrating that the system is sufficiently precise to replace manual measurement and can substantially improve inspection efficiency while evaluating railway fastener looseness.

Indexed as

fastener looseness detectionkernel density estimationnon-contact methodspoint cloud processingrail fastener, railway safety inspectionridge regression

Identifiers

PMID36992010
PMCPMC10051881

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.