- Tytuł:
- Local binary pattern defect recognition approach for the friction stir welded AA 1200 and AA 6061-T6 aluminum alloy
- Autorzy:
- Mishra, Akshansh
- Powiązania:
- https://bibliotekanauki.pl/articles/95297.pdf
- Data publikacji:
- 2020
- Wydawca:
- Politechnika Koszalińska. Wydawnictwo Uczelniane
- Tematy:
-
local binary patterns
friction stir welding
machine learning
surface defects
lokalne wzorce binarne
zgrzewanie tarciowe z mieszaniem materiału
zgrzewanie tarciowe z przemieszaniem
FSW
uczenie maszynowe
wady powierzchni - Opis:
- The research reported in this paper focuses on the application of local binary patterns (LBPs) for surface defects detection. The surface defection detection algorithm for friction stir welded aluminum plates is the key part of the entire surface defect recognition system. Two different grades i.e AA 1200 and AA 6061 plates were similarly joined with the help of Friction Stir Welding process. Python codes for the proposed algorithm were executed on Google Colaboratory platform. The results obtained prove that the local binary patterns method can be used for real-time surface defects detection in friction stir welded joints.
- Źródło:
-
Journal of Mechanical and Energy Engineering; 2020, 4, 1; 27-32
2544-0780
2544-1671 - Pojawia się w:
- Journal of Mechanical and Energy Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł