Dynamics of Structures with Piezoelectric Sensors and Actuators for Structural Health Monitoring
Bibliographic record
Abstract
The dynamic analysis of structures with piezoelectric sensors and actuators is used in this paper to establish a method for crack detection in aerospace structures. Piezoelectric strips used as sensors and actuators are bonded on both sides of a thin structure which executes flexural oscillations. The differential voltage outputs of the piezoelectric sensors are used to detect the presence of cracks in the structure. The structural analysis uses a finite element formulation for the piezoelectric strips coupled with the structure and a nonlinear model for the cracks. This paper presents first the results of the dynamic analysis in the frequency domain of healthy and cracked plates undergoing forced flexural vibrations generated by a pair of piezoelectric actuators submitted to an oscillatory voltage excitation. The peaks in the differential voltage output obtained in the case of a cracked plate at several frequencies during the frequency sweep were found to be indicative measures for the presence of a crack in the structure. The results of the dynamic analysis in the time domain have also shown that this method has a good sensitivity in detecting cracks in the structures.
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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".