Eddy Current Sensor Probe Design for Subsurface Defect Detection in Additive Manufacturing
Bibliographic record
Abstract
Pore and crack formation in parts produced by additive manufacturing (AM) processes, such as laser powder bed fusion, is one of the issues associated with AM technology. Surface and subsurface cracks and pores are induced during the printing process, undermining the printed part durability. In-situ detection of defects will enable the real-time or intermittent control of the process, resulting in higher product quality. In this paper, a new eddy current-based probe design is proposed to detect these defects in parts with various defects that mimic pores and cracks in additively manufactured parts. Electromagnetic finite element analyses were carried out to optimize the probe geometry, followed by fabricating a prototype. Artificial defects were seeded in stainless steel plates to assess the feasibility of detecting various flaws with different widths and lengths. The smallest defect detected had a 0.17 mm radius for blind holes and a 0.43 mm notch with a 5 mm length. All the defects were 0.5 mm from the surface, and the probe was placed on the back surface of the defects. The surface roughness of the tested samples was less than 2 µm. The results show promise for detecting defects, indicating a potential application in AM.
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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".