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Record W2381330046

Design and Research of an Optical Fiber F-P Ultrasound Sensor with High Directivity Sensitivity

2015· article· en· W2381330046 on OpenAlexaff
Shan Nin

Bibliographic record

VenueChuangan jishu xuebao · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsDirectivityOpticsFiber optic sensorOptical fiberWavelengthAmplitudeLaserMaterials scienceSIGNAL (programming language)Ultrasonic sensorSensitivity (control systems)AcousticsPhysicsComputer scienceEngineeringElectronic engineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Optical fiber F-P ultrasound sensor deviates from working point easily in practical applications. The system of low fineness optical fiber F-P sensor is designed based on the technique of dual wavelength stabilization. A dual wavelength optical fiber F-P sensing system mathematical model of DE algorithm is set up. The sensing system with higher quadrature precision is optimized and designed. Laser ultrasound detection system is established based on the sensor. Experimental research on the effectiveness of the sensor to detect ultrasonic signal sensitivity and direction is processed. The results show this sensor can detect ultrasound surface wave signals availably. The amplitude of surface wave is the biggest when the angle between laser source and sensor's axial direction is zero degree.And the amplitude of surface wave decreases along with increasing the angle between laser source and sensor's axial direction. The amplitude descends 80% when the angle between laser source and sensor's axial direction is ninety degree. These demonstrate that the sensor has sensitive directivity.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.288
Teacher spread0.239 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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