High-Efficiency Random Fiber Laser Based on Strong Random Fiber Grating for MHz Ultrasonic Sensing
Bibliographic record
Abstract
An Erbium-gain random fiber laser based on a strong random fiber grating (RFG) is experimentally demonstrated and applied to MHz ultrasound wave detection. The strong RFG with up to −10 dB reflectivity as well as a highly-doped Erbium doped fiber (HD-EDF) enabled a highly efficient random laser radiation with 1-kHz narrow linewidth. With the RFG as the feedback and the sensing head, both burst and continuous ultrasonic signals of up to 8 MHz can be demodulated by dynamics analysis from the random lasing emission. Results show that the detected signal-to-noise ratio (SNR) of 5.1 MHz ultrasound signal remains larger than 43 dB. The proposed random fiber laser sensor provides a broad ultrasonic bandwidth, high sensitivity, simple structure, low cost and robustness to the harsh environment, suggesting prospective applications for ultrasonic wave-associated acoustic emission (AE) detection in structure health monitoring and biomedical diagnosis.
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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 | 0.000 | 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".