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Record W2948245629 · doi:10.11159/iccste19.194

Optical fibre bending sensor for vehicle weight detection

2019· article· en· W2948245629 on OpenAlexvenueno aff
Jan Jargus, Stanislav Kepák, Jakub Čubík, David Bujdoš, Martin Stolárik

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsnot available
FundersMinisterstvo Průmyslu a ObchoduMinisterstvo Školství, Mládeže a Tělovýchovy
KeywordsNatural rubberMaterials scienceBendingSensitivity (control systems)Composite materialAttenuationDetectorAcousticsVibrationOpticsElectronic engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This article describes vehicle detection sensor based on optical fibre bending. Initial measurements were performed on a Heckert FP 10/1 press. Based on these measurements, a prototype of a bending sensor for vehicle detection was designed. This prototype is intended primarily for static vehicle detection, where the magnitude of attenuation is proportional to the weight of the car. When measuring on this prototype, we tested 4 types of ethylene propylene diene methylene (EPDM) grooved rubber that pressed on an optical fibre located on smooth EPDM rubber base. Based on the measurements, we chose the EPDM rubber cover for which the detector had the greatest sensitivity. These initial results indicate that this can be a life-capable structure with a possible extension to a static weight sensor and, partly, to a WIM (weigh in motion) dynamic weight sensor.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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 teacher head, 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

Citations4
Published2019
Admission routes1
Has abstractyes

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