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Record W2056300004 · doi:10.1109/aim.2012.6266004

Intermittent wiring fault detection and diagnosis for SSPC based aircraft power distribution system

2012· article· en· W2056300004 on OpenAlexaff
Anil Yaramasu, Yi Cao, Guangjun Liu, Bin Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFault (geology)Power (physics)Fault indicatorComputer scienceFault detection and isolationEngineeringReliability engineeringElectronic engineeringElectrical engineeringGeology

Abstract

fetched live from OpenAlex

Intermittent wiring faults may happen in aircraft power systems in an unpredictable manner when degraded wires are wet, vibrating against metal structures, or under mechanical stress, etc. They could evolve into serious faults that may cause catastrophic incidents and thus have raised much concern. In this paper, the AB CD method is introduced to derive normal and faulty wire models with reduced complexity compared to conventional differential equation approaches. An intermittent fault detection method is proposed based on estimation of the load circuit model coefficients and parameters utilizing the spectrum information of the high-frequency signals associated with intermittent wiring faults. Furthermore, based on the faulty wiring model, a genetic algorithm is proposed to estimate the fault related wiring parameters such as fault location and resistance. The feasibility of the proposed methods has been verified by simulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.214
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2012
Admission routes1
Has abstractyes

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