Performances comparison of a laser ultrasonic system using 10.6 µm infrared or 532 nm visible generation beam for the investigation of CFRP
Bibliographic record
Abstract
The investigation of complex shaped carbon fiber parts is a common need of the industry. Classical ultrasonic systems are commonly used, wide-spread and very efficient. However, these techniques are often limited to simple shape objects. Major problems arise when the shape of the element to be investigated is complex (peak, valley, small radius of curvature…). To overcome these problems laser ultrasonic systems can be used and the recent developments show promising results. Laser ultrasonic systems can use different wavelengths for ultrasound generation. Usually CO2 lasers emitting at 10.6 µm wavelength are used. When a laser ultrasonic system is mounted on a robotic arm, very complex shaped objects can be considered. However, the optical fibers for 10.6 µm wavelength are not capable to cope with laser ultrasonic system requirements. Therefore, infrared systems use jointed articulated beam delivery systems which reduce the flexibility of the robot arm and significantly limit the feasible scan paths. To circumvent this limitation, an all-fibered laser ultrasonic system can be used. In our case the ultrasound is generated with a pulsed laser operating at 532 nm. This system is placed on a robotic arm, the beam delivery is performed through an optical fiber only. Therefore, this system is capable of analyzing very complex shaped objects due to the use of optical fiber only for laser beam transport. But visible generation is known to be less efficient and produces lower quality signals. In order to balance the advantages and limitations of both of these systems a CFRP plate including artificial defects has been investigated with different ultrasonic systems. First we used classical phased-array ultrasounds as a reference to compare the performances of visible and infrared generation systems. The plate has then been investigated with a 10.6 µm laser ultrasonic system. The results are compared with an all-fibered laser ultrasonic system working at 532 mn wavelength. Data acquired by each system allow comparing the visibility of the ultrasonic echoes and the amplitude of background noise. We observe the impact of frequency filtering. We show the main differences on the A-scans and C-scan generated by each system. From these elements, we show the advantages and limitations of each system for the investigation of CFRP with a focus on complex shaped object.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".