Development of a fiber optic torque sensor and a single channel, high precision optical strain measurement platform
Bibliographic record
Abstract
Fiber optic sensors based on Fiber Bragg Grating (FBG) technology have been successfully adopted for sensor measurements for almost two decades. The advantages offered by FBG sensors, such as Electro-Magnetic Interference immunity and inherent intrinsic safety, provide motivation for the development of a commercial measurement platform. With the development of an FBG Fabry-Perot cavity, a sensor with sub-picometer spectral width allows for a factor of 1000 times improvement in strain measurement. This thesis presents the development of a highly-accurate optical measurement platform based on the FBG Fabry-Perot cavity and Pound-Drever-Hall (PDH) laser locking technique that is demonstrated through the development of an optical torque sensor. With the fiber optic sensor designed as per the PDH requirements, the platform achieved a measurement accuracy of +/-0.015% of the full-scale torque value of 188N∙m. With the platform at ~$2,000, a successful demonstration of the platform and a fiber optic torque sensor is presented.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".