Design and Simulation of Apodized π-Phase Shifted FBG as Simultaneous Sensing of Strain, Temperature, and Vibration
Bibliographic record
Abstract
Bragg Gratings (FBGs) in Structural Health Monitoring (SHM) are used as an optical sensor to detect various physical phenomena to make the system more reliable and accurate. In this work, theoretical analysis and numerical simulation of an Apodized π-Phase Shifted Fiber Bragg Grating (π-PS FBG) sensor is proposed to evaluate the performance of this non-uniform FBG for simultaneous strain, temperature, and vibration sensing. Due to the accuracy and spectral characteristics of π-PS FBG, it's chosen as an optical sensor to enhance the sensibility measurements. The sensor signals designed and simulated by solving coupled mode equations using transfer matrix method in MATLAB to represent the reflected spectrum of PS FBG. As a spectral improvement purpose, the Gaussian apodization function is applied on FBG reflection spectrum to optimize spectra by supressing side lobes. Lastly, the reference FBG method calculation is used to separate vibration and temperature effects from the strain measurements.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".