Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "warunki obróbki" wg kryterium: Temat


Wyświetlanie 1-1 z 1
Tytuł:
Prediction of Surface Roughness based on the Machining Conditions with the Effect of Machining Stability
Autorzy:
Lin, Yung-Chih
Chen, You-Chen
Wu, Kung-Da
Hung, Jui-Pin
Powiązania:
https://bibliotekanauki.pl/articles/102332.pdf
Data publikacji:
2020
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
machining conditions
machining stability
regression analysis
surface roughness
warunki obróbki
stabilność obróbki
analiza regresji
chropowatość powierzchni
Opis:
This study was aimed at analyzing the influence of the cutting parameters (spindle speed, feed rate and cutting depth) on the surface roughness of the machined parts with the influence of the machining stability of the cutter. In order to consider the chattering effect, the machining stabilities were calculated based on the measured tool tip frequency response functions. A series of machining tests were conducted on aluminum workpieces under different cutting parameters. Then, the surface roughness prediction models in the form of nonlinear quadratic and power-law functions were established based on the multivariable regression method, in which the input parameters, cutting depth and spindle speed, were respectively defined in the stable and unstable regions, according to the stability lobes diagram. The current results show that both models built with the cutting parameters defined in stable regions demonstrate higher prediction accuracy of the surface roughness, about 90%, when compared with the models defined in full regions with the accuracy of about 80%. In particular, the power-law model is proven to have 90% prediction accuracy when validated with the cutting parameters in a stable region. As a conclusion, the mathematical models based on the cutting parameters with well-defined machining stability were proven to show more accurate prediction ability of the surface roughness. It could be expected that the prediction model can further be applied to optimize the machining conditions in low speed roughing and high speed finishing process with desirable surface quality.
Źródło:
Advances in Science and Technology. Research Journal; 2020, 14, 2; 171-183
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-1 z 1

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies