Evidence map›Paper›PMID 36679844›Full record

ArticleSensors (Basel, Switzerland)2023

Multirotor Motor Failure Detection with Piezo Sensor.

Leszek Ambroziak, Daniel Ołdziej, Andrzej Koszewnik

Open access · goldAbstract 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. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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

7 citing papers in PubMed, 29 citations in OpenAlex.

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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 at 1 institution in 1 country.

Leszek AmbroziakDepartment of Robotics and Mechatronics, Faculty of Mechanical Engineering, Bialystok University of Technology, Wiejska St. 45C, 15-351 Bialystok, Poland.ORCID 0000-0001-7612-768X
Daniel OłdziejDepartment of Robotics and Mechatronics, Faculty of Mechanical Engineering, Bialystok University of Technology, Wiejska St. 45C, 15-351 Bialystok, Poland.ORCID 0000-0001-5412-4752
Andrzej KoszewnikDepartment of Robotics and Mechatronics, Faculty of Mechanical Engineering, Bialystok University of Technology, Wiejska St. 45C, 15-351 Bialystok, Poland.ORCID 0000-0001-6430-6007
Bialystok University of Technology · PL

Funding

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

Abstract

Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system.

Indexed as

SportsData CollectionReproducibility of ResultsUnmanned Aerial DevicesVibrationdetectiondiagnosticsmotor failuremultirotorpiezo sensorunmanned aerial vehiclesvibration analysis

Identifiers

PMID36679844
PMCPMC9862776
OpenAlexW4316672850

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.