- Tytuł:
- Monitoring of the average cutting forces from controller signals using artificial neural networks
- Autorzy:
-
Bugdayci, Nevzat Bircan
Wegener, Konrad
Postel, Martin - Powiązania:
- https://bibliotekanauki.pl/articles/2171771.pdf
- Data publikacji:
- 2022
- Wydawca:
- Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
- Tematy:
-
milling
cutting force monitoring
artificial neural network - Opis:
- A new approach is presented to monitor the average cutting forces that are used for the calculation of the average cutting coefficients through neural networks using available controller signals. The cutting forces and the relevant controller signals are measured using a dynamometer and commercially available software supplied by the controller manufacturer in the calibration stage. Then a neural network is trained, which treats these controller signals as inputs and the cutting forces as the outputs. Finally, the average cutting forces for a new milling operation are predicted using the trained neural network without using a dynamometer. The proposed approach is validated using an experimental study, where a good match between predictions and measured forces is achieved. It is also shown that cutting coefficients can be calibrated and stability lobe diagrams can be generated using this method.
- Źródło:
-
Journal of Machine Engineering; 2022, 22, 4; 54--70
1895-7595
2391-8071 - Pojawia się w:
- Journal of Machine Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł