- Tytuł:
- Artificial neural network modelling of vibration in the milling of AZ91D alloy
- Autorzy:
-
Zagórski, I.
Kulisz, M.
Semeniuk, A.
Malec, A. - Powiązania:
- https://bibliotekanauki.pl/articles/102005.pdf
- Data publikacji:
- 2017
- Wydawca:
- Stowarzyszenie Inżynierów i Techników Mechaników Polskich
- Tematy:
-
magnesium alloys
high-speed dry milling
vibration
chatter in milling
simulation
artificial neural networks - Opis:
- The paper reports the results of artificial neural network modelling of vibration in a milling process of magnesium alloy AZ91D by a TiAlN-coated carbide tool. Vibrations in machining processes are regarded as an additional, absolute machinability index. The modelling was performed using the so-called “black box” model. The best fit was determined for the input and output data obtained from the machining process. The simulations were performed by the Statistica software using two types of neural networks: RBF (Radial Basis Function) and MLP (Multi-Layered Perceptron).
- Źródło:
-
Advances in Science and Technology. Research Journal; 2017, 11, 3; 261-269
2299-8624 - Pojawia się w:
- Advances in Science and Technology. Research Journal
- Dostawca treści:
- Biblioteka Nauki
Artykuł