Microwave Photonic Interrogation of a High-Speed and High-Resolution Temperature Sensor Based on Cascaded Fiber-Optic Sagnac Loops
Bibliographic record
Abstract
A high-speed and high-resolution temperature sensor based on two cascaded fiber-optic Sagnac loops (FSLs) interrogated using a microwave photonic (MWP) method is proposed and experimentally demonstrated. In the proposed system, an FSL is used as a sensor element. When it is experiencing temperate change, its spectrum is shifted, which leads to the shift in the spectrum of the cascaded FSLs. Instead of measuring the wavelength shift of the spectrum by using an optical spectrum analyzer (OSA), which has a low wavelength resolution and a slow scanning speed, we convert the optical spectrum to the time domain based on spectral shaping and wavelength-to-time (SS-WTT) mapping, and use a digital signal processor (DSP) to extract the sensing information. In our experiment, two cascaded FSLs with two different free spectrum ranges (FSRs) are employed. Due to the Vernier effect, multiple dips in the envelope of the optical spectrum are introduced. By passing a broadband frequency-chirped optical pulse generated by a frequency-swept laser source to the two cascaded FSLs, the sensing information is encoded in the optical spectrum and it is converted to the time domain due to SS-WTT mapping. By detecting the optical waveform at a photodetector (PD), a temporal microwave waveform with its shape identical to the optical spectrum is generated. By using a DSP, the time shift of a dip is measured and the sensing information is precisely demodulated. Experimental result shows that the proposed fiber-optic temperature sensor can provide a temperature resolution of 1.33 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−5</sup> °C at a sensing speed of 23.497 kHz.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".