Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: workpiece deformations

Sortuj według:

Ogranicz wyniki do:

Classification of Deflections of Thin-Walled Elements Made of EN AW-7075A Aluminum Alloy During Milling

Czyżycki Jakub, Marciniak-Podsadna Lidia, Twardowski Paweł

Advances in Science and Technology. Research Journal

2023

Vol. 17, no 6

301--314

The aim of the research is to classify and evaluate the size of deformations appearing during milling of thin-walled elements representing a pocket form made of aluminum alloy AW-7075A. Finishing, which is the purpose of the research, was carried out at the full depth of cut ap = 15 mm, milling the entire height of the wall in one pass. Deformations during machining were correlated with the geometric accuracy of the workpieces after machining. During the tests, deformations were measured with a laser displacement sensor, and the temperature of the samples was measured using a resistance temperature sensor. The tests made it possible to identify deformations occurring during the milling of thin-walled elements. The course of deformation during milling was analyzed, from which the value of deformation caused by milling, the reaction to this deformation and its time were extracted, additionally, permanent distortion of the workpiece was detected. The results show the effect of the ratio of the height to the thickness of the thin-walled element on its geometric accuracy after machining in the form of straightness and flatness of the samples. The test results were compared to the tests carried out on the Ti6Al4V titanium alloy, which confirmed the influence of the material selection on the course of deformations during milling.

Zastosowanie sieci neuronowych do modelowania odksztalcen przedmiotu obrabianego podczas toczenia

Jóźwik J., Lipski J.

Eksploatacja i Niezawodność

2002

nr 4(16)

30-39

W artykule wskazano na szerokie możliwości modelowania procesów skrawania za pomocą strategii samouczenia. Zaprezentowano model predykcji sumarycznych odkształceń przedmiotu obrabianego za pomocą sztucznych sieci neuronowych. Badania i analizy przeprowadzono na przykładzie toczenia ortogonalnego tulei cienkościennej, poddanej działaniu ciepła i sił w procesie skrawania.

In this paper has been to shown wide possibility modeling of cutting process by self-teaching strategy. Hear have been presented neural network model of workpiece summary deformations. Research and analyzes have been shown based on example orthogonal turning of thin-walled sleeve to expose it on action of heat and cutting forces.