- Tytuł:
- Automated evaluation of continuous and segmented chip geometries based on image processing methods and a convolutional neural network
- Autorzy:
-
Klippel, Hagen
Pflaum, Samuel
Kuffa, Michal
Wegener, Konrad - Powiązania:
- https://bibliotekanauki.pl/articles/2171775.pdf
- Data publikacji:
- 2022
- Wydawca:
- Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
- Tematy:
-
machining
AI
computer vision
image processing
chip
chip shape
chip segmentation - Opis:
- The aim of this work is to present a new methodology for the automated analysis of the cross-sections of experimental chip shapes. It enables, based on image processing methods, the determination of average chip thicknesses, chip curling radii and for segmented chips the extraction of chip segmentation lengths, as well as minimum and maximum chip thicknesses. To automatically decide whether a chip at hand should be evaluated using the proposed methods for continuous or segmented chips, a convolutional neural network is proposed, which is trained using supervised learning with available images from embedded chip cross-sections. Data from manual measurements are used for comparison and validation purposes.
- Źródło:
-
Journal of Machine Engineering; 2022, 22, 4; 115--132
1895-7595
2391-8071 - Pojawia się w:
- Journal of Machine Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł