Evidence map›Paper›PMID 30875726›Full record

ArticleSensors (Basel, Switzerland)2019

Robust Identification of Strain Waves due to Low-Velocity Impact with Different Impactor Stiffness.

Alessio Beligni, Claudio Sbarufatti, Andrea Gilioli, Francesco Cadini, Marco Giglio

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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

5 authors.

Alessio BeligniPolitecnico di Milano, Mechanical Engineering Department, via La Masa 1, 20156 Milano, Italy. alessio.beligni@polimi.it.ORCID 0000-0002-7743-9789
Claudio SbarufattiPolitecnico di Milano, Mechanical Engineering Department, via La Masa 1, 20156 Milano, Italy. claudio.sbarufatti@polimi.it.
Andrea GilioliPolitecnico di Milano, Mechanical Engineering Department, via La Masa 1, 20156 Milano, Italy. andrea.gilioli@polimi.it.
Francesco CadiniPolitecnico di Milano, Mechanical Engineering Department, via La Masa 1, 20156 Milano, Italy. francesco.cadini@polimi.it.
Marco GiglioPolitecnico di Milano, Mechanical Engineering Department, via La Masa 1, 20156 Milano, Italy. marco.giglio@polimi.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-velocity impacts represent a major concern for aeronautical structures, sometimes producing barely detectable damage that could severely hamper the aircraft safety, even with regards to metallic structures. For this reason, the development of an automated impact monitoring system is desired. From a passive monitoring perspective, any impact generates a strain wave that can be acquired using sensor networks; signal processing techniques allow for extracting features useful for impact identification, possibly in an automatic way. However, impact wave characteristics are related to the impactor stiffness; this presents a problem for the evaluation of an impact-related feature and for the development of an automatic approach to impact identification. This work discusses the problem of reducing the influence of the impactor stiffness on one of the features typically characterizing the impact event, i.e., the time of arrival (TOA). Two passive sensor networks composed of accelerometers and piezoelectric sensors are installed on two metallic specimens, consisting of an aluminum skin and a sandwich panel, with aluminum skins and NOMEX

Indexed as

data processingfeature selectionimpact identificationimpactor stiffnesslow-velocity impactsstrain wave

Identifiers

PMID30875726
PMCPMC6470595

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.