- Tytuł:
- Parallel cross-section recognition of geometrical features for selected machine parts
- Autorzy:
-
Golaszewski, Marcin
Krolikowski, Marcin
Powalka, Bartosz - Powiązania:
- https://bibliotekanauki.pl/articles/1833767.pdf
- Data publikacji:
- 2021
- Wydawca:
- Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
- Tematy:
-
feature recognition
computer aided reengineering
3D scanning
parametric geometry - Opis:
- Increase of automation and autonomy of production is the latest trend incorporated into Industry 4.0 objectives. Production autonomy is very desirable in the field of damaged parts replacement. To fulfill this goal numerous reverse engineering systems have been developed that support geometry recognition from the 3D scan data. This study is focused on converting non-parametric geometry representation of shaft-type elements into a CAD model with a rebuilt feature tree. Algorithms are based on the analysis of parallel cross-sections. The proposed system is also capable of identification of additional geometric features typical for 2.5 axes milling such as pockets, islands and outer walls. The proposed algorithms are optimized to increase efficiency of the process. Initial identification parameters are selected with respect to defined criteria, e.g., identification accuracy, computing power and scanning accuracy. Described algorithms can be implemented in reverse engineering systems.
- Źródło:
-
Journal of Machine Engineering; 2021, 21, 3; 60--79
1895-7595
2391-8071 - Pojawia się w:
- Journal of Machine Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł