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Record W2027435705 · doi:10.1117/12.567240

Effect of pulsewidth on strain measurement accuracy in Brillouin-scattering-based fiber optic sensors

2004· article· en· W2027435705 on OpenAlexaff
Fabien Ravet, Xiaoyi Bao, Liang Chen

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBrillouin zoneBrillouin scatteringRayleigh scatteringStrain (injury)OpticsMaterials scienceIntensity (physics)ScatteringOptical fiberPhysics

Abstract

fetched live from OpenAlex

Distributed Sensors based on Brillouin scattering are attractive candidates to monitor structural health of mechanical structures. Currently physical limitations of time resolved techniques do not allow extracting accurate strain when pulsewidth is larger than strained length. The purpose of this study was to quantify the errors in such a case and derive a decision threshold making possible the discrimination of strained section from unstrained contribution. We achieved these goals by solving the coupled intensity equations for various strained lengths, pulsewidths, strain strengths, Brillouin linewidths, Fibre lengths, probe and pump powers. We observed two dominating behaviours principally functions of strained length and strain strength. In the first regime, a single peak broader than Brillouin natural gain/loss peak was detected. In the second case, we could distinguish two peaks. From these behaviours we then derived curves relating Brillouin peak contrast as well strain accuracy to the ratio between strained section length and pulsewidth. These curves also show a strong dependence on strain amplitude. This led us to find a strain induced frequency shift threshold characterising the transition from the single peak regime to the double peak regime. Finally we defined a Rayleigh equivalent criterion that unambiguously separates strained from unstrained contributions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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.

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

Citations2
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fiber Optic SensorsFrench-language works237,207