Evidence map›Paper›PMID 32916831›Full record

ArticleSensors (Basel, Switzerland)2020

Novel Higher-Order Spectral Cross-Correlation Technologies for Vibration Sensor-Based Diagnosis of Gearboxes.

Len Gelman, Krzysztof Soliński, Andrew Ball

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

3 authors.

Len GelmanDepartment of Engineering and Technology, The University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK.
Krzysztof SolińskiMeggitt Sensing Systems, Rte de Moncor 4, 1701 Fribourg, Switzerland.
Andrew BallDepartment of Engineering and Technology, The University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK.ORCID 0000-0002-8593-6830

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel vibration sensor-based diagnostic technologies, built on the higher order wavelet spectral cross-correlation (WSC), are proposed, investigated and applied to gearbox vibration diagnosis for the first time in worldwide terms. The proposed WSC-based technologies do not feature any constrains in selection of signal spectral components, relations between which are analysed. That is a radical improvement in comparison with the higher-order spectra (HOS). The WSC technologies are applied for an experimental diagnosis of a local gear tooth fault of a helical gearbox that is developed during a long duration gearbox endurance test. Differences between the applied technologies and advantages of the novel WSC approach over the classical HOS are explained in detail. Superiority of the WSC technologies is justified by high validity comprehensive experimental comparison with the HOS technologies: i.e., the wavelet bicoherence and the wavelet tricoherence.

Indexed as

gearbox fault diagnosis vibration analysiswavelet spectral cross-correlation

Identifiers

PMID32916831
PMCPMC7570882

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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.