A Fiber-Only Optical Vibration Sensor Using Off-Centered Fiber Bragg Gratings
Bibliographic record
Abstract
Vibration monitoring of rotating machinery is crucial for operational safety and optimized maintenance. In this work, we propose a fiber Bragg grating (FBG) vibration sensor that does not involve any other components beyond the optical fiber on which the FBG is inscribed. The optical fiber is supported at one end to form a cantilever arrangement. The FBG is positioned at the support, intentionally offset from the center of the fiber core. Continual bending of the cantilever beam due to vibration induces axial tensile and compressive stresses away from the neutral axis, where the off-centered FBG is located. This causes a reciprocating shift in the FBG’s central wavelength, enabling us to measure the frequency and amplitude of the applied vibration. Since central wavelength is the measurand, the proposed sensor is compatible with wavelength division multiplexing, thereby expanding its utility across diverse industries. The sensor prototype fabricated and tested in this study, performed linearly within a wide range of frequencies (20–1500 Hz), and was responsive to accelerations as low as 0.3 g. The sensor characteristics can be tailored to a specific application by fine-tuning the dimensions and support configurations.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".