Abstract
Originally developed for biomedical applications and diagnosis, optical coherence tomography (OCT) has recently been demonstrated to be a powerful non-destructive and non-invasive measurement method for detecting defects in glass-fiber reinforced polymer composites. While previous studies have focused mainly on the use of OCT in the analysis of thermoset composites, we were able to show in offline experiments that OCT can be used to quickly detect typical defects (e.g., dry fiber regions, gaps and fiber breakage) in thermoplastic unidirectional (UD) tapes at high resolution. To investigate the applicability of OCT to inline monitoring, we advanced our previously published approach in two major steps: First, we incorporated the OCT system into an industrial-scale UD-tape production line, and derived optimal settings for inline detection of dry region defects from a comprehensive design of experiments (DoE) to find an optimal balance between accuracy and data size for a stationary tape sample by varying A-scan sampling rate, A-scan averaging and OCT transverse travel velocity. Second, using these optimal settings, we went on to investigate moving tapes over a range of industrially relevant take-off speeds. Microscopy was used for validation in both cases. We developed a fast and robust statistical analysis of B-scans that visualizes the quality of full cross-sections in an interpretable manner for potential use in a real-time setting. Within an industrially relevant production speed range of up to 15 m/min, we are thus now able to investigate 120 mm wide (and potentially wider) UD tapes inline at a transverse resolution of 22 µm, producing only 21 MB of data per measurement.
| Original language | English |
|---|---|
| Pages (from-to) | 3051-3076 |
| Number of pages | 26 |
| Journal | Journal of Thermoplastic Composite Materials |
| Volume | 38 |
| Issue number | 8 Spec. Iss. |
| Early online date | 20 Aug 2024 |
| DOIs | |
| Publication status | Published - Aug 2025 |
Fields of science
- 205 Materials Engineering
- 205011 Polymer engineering
- 102009 Computer simulation
- 102033 Data mining
- 104018 Polymer chemistry
- 502059 Circular economy
- 205012 Polymer processing
- 104019 Polymer sciences
- 502058 Digital transformation
JKU Focus areas
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management