Acousto-optic material differentiation during water jet-guided laser cutting by applying a neural network
By applying a combination of statistical feature analysis and machine learning we demonstrate the feasibility of detecting different materials in a multi-material layered substrate based on optical and acoustic signatures during water jet-guided laser cutting.
Authors
- Amédée Zryd
- R. Richter (ORCID: https://orcid.org/0000-0003-4781-6421)
- Sergey A. Shevchik (ORCID: https://orcid.org/0000-0003-0073-3450)
- Vigneashwara Pandiyan (ORCID: https://orcid.org/0000-0001-6043-5696)
- P. Hoffmann (ORCID: https://orcid.org/0000-0002-7924-6219)
- Toni Ivas (ORCID: https://orcid.org/0000-0001-8989-065X)
- L. H. DiSalvo
Institutions
- Swiss Federal Laboratories for Materials Science and Technology (CH)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676839
- Primary Topic
- Laser Material Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00