Structural health monitoring strategy for detection of interlaminar delamination in composite plates
Bibliographic record
Abstract
In this paper, a Structural Health Monitoring (SHM) strategy is proposed in order to detect interlaminar delamination in a Carbon Fiber Reinforced Polymer (CFRP) structure using guided waves. The delamination is simulated by inserting a Teflon tape between two transverse plies and the guided wave generation and measurement is ensured by piezoceramic (PZT) elements. Theoretical propagation and through-the-thickness strain distribution are first studied in order to determine the optimal configuration of the final system in terms of mode and frequency selection and piezoceramic spacing for detection of cross-sectional delamination. Finite element simulation are then used to validate the assumptions and pitch and catch measurements are performed by comparing wave propagation for different frequencies and along damaged and undamaged paths and the analysis of results is performed using Reassigned Short-Time Fourier Transform (ReSTFT). It appears that in the low frequency range (below 300 kHz), A0 mode is sensitive to the damage while in the high frequency range, S 1 and A1 modes are both very sensitive to the damage while the propagation of the S 0 mode is not much affected.
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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) | 0.001 | 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".