Evidence map›Paper›PMID 38676256›Full record

ArticleSensors (Basel, Switzerland)2024

Modelling Inductive Sensors for Arc Fault Detection in Aviation.

Gabriel Barroso-de-María, Guillermo Robles, Juan Manuel Martínez-Tarifa, Alexander Cuadrado

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 3 institutions in 1 country.

Gabriel Barroso-de-MaríaAirbus Defence and Space, 28906 Getafe, Spain.ORCID 0000-0001-7212-2750
Guillermo RoblesDepartment of Electrical Engineering, University Carlos III of Madrid, 28911 Leganes, Spain.ORCID 0000-0002-2688-9202
Juan Manuel Martínez-TarifaDepartment of Electrical Engineering, University Carlos III of Madrid, 28911 Leganes, Spain.ORCID 0000-0001-9671-9818
Alexander CuadradoEscuela de Ciencias Experimentales y Tecnología, University Rey Juan Carlos, 28008 Madrid, Spain.ORCID 0000-0001-6277-2426
Universidad Carlos III de Madrid · ESAirbus (Spain) · ESUniversidad Rey Juan Carlos · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern aircraft are being equipped with high-voltage and direct current (HVDC) architectures to address the increase in electrical power. Unfortunately, the rise of voltage in low pressure environments brings about a problem with unexpected ionisation phenomena such as arcing. Series arcs in HVDC cannot be detected with conventional means, and finding methods to avoid the potentially catastrophic hazards of these events becomes critical to assure further development of more electric and all electric aviation. Inductive sensors are one of the most promising detectors in terms of sensitivity, cost, weight and adaptability to the circuit wiring in aircraft electric systems. In particular, the solutions based on the detection of the high-frequency (HF) pulses created by the arc have been found to be good candidates in practical applications. This paper proposes a method for designing series arc fault inductive sensors able to capture the aforementioned HF pulses. The methodology relies on modelling the parameters of the sensor based on the physics that intervenes in the HF pulses interaction with the sensor itself. To this end, a comparative analysis with different topologies is carried out. For every approach, the key parameters influencing the HF pulses detection are studied theoretically, modelled with a finite elements method and tested in the laboratory in terms of frequency response. The final validation tests were conducted using the prototypes in real cases of detection of DC series arcs.

Indexed as

all-electric aircraftfinite elements methodinductive sensorsmodellingmore-electric aircraftseries arcs

Identifiers

PMID38676256
PMCPMC11054130
OpenAlexW4395002497

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.