Inductive and solid-state sensing of pulsed eddy current: A comparative study
Bibliographic record
Abstract
In recent years, solid-state devices made their way in the development of electromagnetic non-destructive evaluation (NDE) probes. This fact was evidenced especially for pulsed eddy current, where magneto-resistive and Hall effect devices are used as sensing elements. Their low frequency range and small surface area are suitable to improve the detection of buried and small discontinuities. Although their properties are expected to enhance detectability over simple induction coils, this was still to be proven or demonstrated in a comparative study. This work compares the sensing capabilities of an induction coil to those of two solid-state devices: giant-magneto-resistive (GMR) and Hall effect sensors. All of them are used as detectors in pulsed eddy current probes that have the same excitation mechanism, a ring-type copper coil driven by a constant amplitude square waveform. While the excitation part of the probe is fixed, the sensing components are inter-changeable. Although both induction coils and solid-state sensors output a voltage value as an indication of the magnetic field they are detecting, the voltage for pick-up coils is directly proportional to the rate of change of the magnetic flux. For solid-state sensors the output is in direct relation to the detected magnetic field. Under this study, all three sensing elements are used to detect the driving coil's magnetic output (magnetic field or flux) in air, on planes perpendicular and parallel to the face of the driver coil. The results obtained by all three sensors are quantitatively compared. Then the sensing devices are inserted in the inner space of the driving coil and, subsequently, used for detection of artificially made defects. Finally, the results are compared in terms of magnetic field sensitivity and inspection performance.
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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".