Measurement of paint and coating thickness on metallic plates using smart near field microwave sensor
Bibliographic record
Abstract
A smart microwave sensor for non-destructive thickness measurement of paint and dielectric coating of metallic plates is presented. The sensor is based on low cost microstrip transmission line with a Complementary Split-Ring Resonator (CSRR) in the ground plan. The CSRR sensor experiences a frequency shift proportional to the thickness of a dielectric layer backed with metallic plate as described. Ideally, one would like the frequency shift to be related directly to a thickness reading (usually in mm or um). An artificial intelligent regression model was developed to automate the post processing of the measurements and achieve actual thickness data. This work presents simulation, measurements, and data post-processing of CSRR sensor operating on metallic plate with different coating thicknesses. The post-processing was performed using Support Victor Regression (SVR) algorithm on the transmission coefficients.
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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".