Non-contact Ice Detection Using Waveguide Sensor at 12.4-18 GHz Frequency Span
Bibliographic record
Abstract
Ice detection, icing prevention, and removal are considered vital issues in many applications, particularly in the aviation industry. This work presents a WR-62 waveguide-based detection sensor to monitor icing and to detect and distinguish between water and ice on metallic and non-metallic surfaces. The difference between the dielectric properties of water and ice makes the proposed waveguide-based probe an accurate sensor for the ice accretion monitoring purpose. The sensor operates based on tracking the scattering parameter of the reflection coefficient (S<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</inf>), and the frequency response of the waveguide at 13.48 GHz. The proposed waveguide probe system has the capability of non-contact detecting ice formation over various surfaces and can be mounted on industrial drones for autonomous inspection purposes.
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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) | 0.000 | 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) | 0.000 | 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".