Tilted fiber grating accelerometer incorporating an abrupt biconical taper for cladding to core recoupling
Bibliographic record
Abstract
We demonstrate a compact power-referenced fiber-optic accelerometer using a weakly tilted fiber Bragg grating (TFBG) combined with an abrupt biconical taper. The electric-arc-heating induced taper is located a short distance upstream from the TFBG and functions as a bridge to recouple the TFBG-excited lower-order cladding modes back into the fiber core. This recoupling is extremely sensitive to microbending. We avoid complex wavelength interrogation by simply monitoring power change in reflection, which we show to be proportional to acceleration. In addition, the Bragg resonance is virtually unaffected by fiber bending and can be used as a power reference to cancel out any light source fluctuations. The proposed sensing configuration provides a constant linear response (nonlinearity < 1%) over a vibration frequency range from DC to 250 Hz. The upper vibration frequency limit of measurement is determined by mechanical resonance, and can be tuned by varying the sensor length. The tip-reflection sensing feature enables the sensor head to be made small enough (20~100 mm in length and 2 mm in diameter) for embedded detection. The polymer-tube-package makes the sensor sufficiently stiff for in-field acceleration measurement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".