Characterization and application of Brillouin scattering-based distributed fiber optic sensor
Bibliographic record
Abstract
Brillouin scattering based distributed fiber optic sensing as a novel technique has attracted much attention in both research and application for the past ten years. The fiber optic group at the University of Ottawa has developed an advanced automatic Brillouin sensing system and improved it continuously. This thesis presents the characterization and optimization of this sensing system and a series of successful applications both in the laboratory and in the field. Several parameters have been studied around the pulse generation subsystem: such as, bias, leakage, PW voltage, pulsewidth, and repetition frequency. Bias is found to be the most important parameter. We also discuss the relationships between the system repeatability and control parameters such as bias, polarization states, averages and frequency lock methods. Four successful applications of the distributed Brillouin sensing system are reported in the thesis. They are strain measurement in a reinforced concrete beam, simultaneous strain and temperature monitoring of composite curing process, strain and temperature monitoring of a concrete structure, and temperature compensated strain measurement of the load test on the Rollinsford Bridge.
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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 | 0.001 |
| 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) | 0.001 | 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".