Evidence map›Paper›PMID 39060427›Full record

ArticleScientific reports2024

Diagnostics of unmanned aerial vehicle with recurrence based approach of piezo-element voltage signals.

Bartłomiej Ambrożkiewicz, Paweł Dzienis, Leszek Ambroziak, Andrzej Koszewnik, Arkadiusz Syta, Daniel Ołdziej, Vikram Pakrashi

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

7 authors.

Bartłomiej AmbrożkiewiczFaculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Białystok, Poland. b.ambrozkiewicz@pollub.pl.
Paweł DzienisFaculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Białystok, Poland.
Leszek AmbroziakFaculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Białystok, Poland.
Andrzej KoszewnikFaculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Białystok, Poland.
Arkadiusz SytaDepartment of Technical Computer Science, Faculty of Mathematics and Technical Computer Science, Lublin University of Technology, Nadbystrzycka 38, 20-618, Lublin, Poland.
Daniel OłdziejFaculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Białystok, Poland.
Vikram PakrashiCentre for Mechanics, School of Mechanical and Materials Engineering, University College Dublin, Stillorgan Road, Belfield, Dublin 4, Republic of Ireland.

Funding

Ministerstwo Edukacji i Nauki MEiN/2022/DPI/2575Ministerstwo Edukacji i Nauki WZ/WM-IIM/2/2022
6 · The paper itself

Abstract

This work experimentally addresses damage calibration of an unmanned aerial vehicle in operational condition. A wide range of damage level and types are simulated and controlled by an electric motor via pulse width modulation in this regard. The measurement is carried out via established protocols of using a piezo-patch on one of the 8 arms, utilising the vibration sensitivity and flexibility of the arms, demonstrating repeatability of such protocol. Subsequently, recurrence analysis on the voltage time series data is performed for detection of damage. Quantifiers of damage extent are then created for the full range of damage conditions, including the extreme case of complete loss of power. Experimental baseline condition for no damage condition is also established in this regard. Both diagonal-line and vertical-line based indicators from recurrence analysis are sensitive to the quantitative estimates of damage levels and a statistical test of significance analysis confirms that it is possible to automate distinguishing the levels of damage. The damage quantifiers proposed in this paper are useful for rapid monitoring of unmanned aerial vehicle operations of connection.

Indexed as

Damage calibrationElectric motor failureMechanical vibrationsPiezoelectric sensorRecurrence analysisUnmanned aerial vehicle

Identifiers

PMID39060427
PMCPMC11282262

What OpenQuestion holds

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LicenceCC BY
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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.