Nondestructive Phase Variation-Based Chipless Sensing Methodology for Metal Crack Monitoring
Bibliographic record
Abstract
This article presents a new methodology for structural health monitoring (SHM) applications using a passive microwave sensor. This sensor provides sensitivities on metallic structures for nondestructive testing (NDT) and detecting fatigue cracks or damages. In this method, two different microstrip-based designs are mounted on metal, spiral, and comb sensing structures. Both sensing structures are interrogated by a 2.45 GHz signal in CST Microwave Studio, and their sensitivities for crack detection are compared through the$S_{11}$scattering parameter. We demonstrate that measuring the reflected signal’s phase parameter from a sensor on a damaged metal provides information from the surface crack by comparing it to the same metal without any crack. The vision is to provide a new chipless, low-cost sensor with increased detection reliability and durability in harsh environments. Simulation results of the comb sensing (CS) structure show that the signal phase shift caused by a crack envisions the possibility of submillimeter-width crack detection through smart 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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 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".