Digital demodulation system for low-coherence interferometric sensors based on highly birefringent fibers
Bibliographic record
Abstract
A new type of demodulation system for low-coherence interferometric sensors based on highly birefringent fibers is presented. The optical path delay introduced by the sensor is compensated in four detection channels by quartz crystalline plates of appropriate thickness. The system can be used to decode a single-point sensor with a resolution of 2.5 x 10(-3) or two serially multiplexed sensors with decreased resolution. In a multiplexed configuration each sensor is served by two detection channels. By tilting the quartz plates, we can tune the initial phase shift between interference signals in successive channels to differ by pi/8 or pi/4, respectively, for a single-point or a multiplexed configuration. We transferred the sinusoidal intensity changes into digital pulses by appropriate electronic processing, which eventually allows for an unambiguous phase-shift measurement with a resolution of 1/8 or 1/4 of an interference fringe. The system performance for the measurement of hydrostatic pressure changes and simultaneous changes of hydrostatic pressure and temperature is demonstrated. The pressure sensors are based on side-hole fiber to ensure high sensitivity and an operation range of 2.4 MPa. A new configuration for temperature compensation of hydrostatic pressure sensors is proposed, which is better suited for dynamic pressure measurements. In this configuration the sensing and compensating fibers are located in the same compartment of the sensor housing.
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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 | 0.001 | 0.001 |
| 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".