Poling Process of Composite Piezoelectric Sensors for Structural Health Monitoring: A Pilot Comparative Study
Bibliographic record
Abstract
Piezoelectric transducers are widely used as sensors and actuators, benefiting from their well-known smart asset of energy conversion. Synthesized piezoelectric materials, including thin/thick films and stacked wafers, are subject to a process, called poling, before implementation. The poling process significantly helps to resuscitate or enhance the piezoelectric properties of a deteriorated semi-isotropic structure by activating/energizing the dipoles. The poling process consists of exposing the piezoelectric films/wafers to high electric field to apply external energy to the granular structures and, thus, enhance the piezoelectric response. This article reports the results obtained during the poling process of composite piezoelectric films with different sizes and thicknesses, which are deposited on the curved surface of superalloy blades in order to conduct structural health monitoring. This article also studies effects of parameters such as poling temperature, applied electric field, polarizing time, porosity, and film size on electric, ferroelectric, and piezoelectric properties of different specimens. Experiments are conducted by controlling annealing time, temperature, and, thus, grain size, while nitrogen gas is blown into the tube furnace at the time the samples are thermally treated after deposition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".