Detection of Internal Holes in Additive Manufactured Ti-6Al-4V Part Using Laser Ultrasonic Testing
Bibliographic record
Abstract
For a non-contact, non-destructive quality evaluation, laser ultrasonic testing (LUT) has received increasing attention in complex manufacturing processes, such as additive manufacturing (AM). This work assessed the LUT method for the inspection of internal hole defects in additive manufactured Ti-6Al-4V part. A Q-switched pulsed laser was utilized to generate ultrasound waves on the top surface of a Ti-6Al-4V alloy part, and a laser Doppler vibrometer (LDV) was utilized to detect the ultrasound waves. Sub-millimeter (0.8 mm diameter) internal hole defect was successfully detected by using the established LUT system in pulse-echo mode. The method achieved a relatively high resolution, suggesting significant application prospects in the non-destructive evaluation of AM part. The relationship between the diameter of the hole defects and the amplitude of the laser-generated Rayleigh waves was studied. X-ray computed tomography (XCT) was conducted to validate the results obtained from the LUT system.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".