A Holistic Approach to Structural Health Monitoring of Composite Aerospace Structures using Lamb Waves: From Manufacturing to Service
Bibliographic record
Abstract
The successful application of a structural health monitoring (SHM) system for composite aerospace structures requires a holistic approach encompassing the full life cycle of the structure. Important capabilities of an SHM system include: 1) recognition, 2) identification, 3) severity, and 4) location of a defect. This was achieved, first, by designing a novel manufacturing method to co-cure piezoelectric sensors to the surface of carbon fibre reinforced polymer (CFRP) panels, allowing for in-situ cure monitoring, manufacturing inspection, and in-service monitoring. Second, numerical and experimental techniques used Lamb wave propagation to recognize and identify multiple types of manufacturing defects and determine the severity of a delamination defect. A comparison of co-cured and bonded piezoelectric sensors showed similar waveform shape, Lamb wave propagation velocity, and signal amplitude for the anti-symmetric Lamb wave mode. Performing a time-frequency domain analysis using the continuous wavelet transform demonstrated the ability to recognize and identify delamination, porosity, and foreign object defects. To determine the severity of a delamination defect, five input signals were compared and it was determined the Mexican hat excitation provided the best average main lobe width resolution and signal-to-noise ratio over a range of frequencies, particularly at lower frequencies. Finally, a multiple level discrete wavelet transform decomposition was able to provide signal compression, up to 450 times, while still maintaining the important signal features to determine the severity of a delamination defect. This allowed both the length ratio and depth sequence of multiple delamination defects to be correctly identified. The practical approach of this research to focus on the manufacturing process and manufacturing defects provided an important step towards a holistic SHM system for CFRP structures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".