ISJ Theoretical & Applied Science 05(121) 2023

Philadelphia, USA

Egamberdiev, I. P., Ochilov, U. Yu., & Irnaeva, L. S.

Simulation of the connection between machine components using the distributed parameters method.

Full Article: PDF

Scientific Object Identifier: http://s-o-i.org/1.1/TAS-05-121-33

DOI: https://dx.doi.org/10.15863/TAS.2023.05.121.33

Language: Russian

Citation: Egamberdiev, I. P., Ochilov, U. Yu., & Irnaeva, L. S. (2023). Simulation of the connection between machine components using the distributed parameters method. ISJ Theoretical & Applied Science, 05 (121), 177-183. Soi: http://s-o-i.org/1.1/TAS-05-121-33 Doi: https://dx.doi.org/10.15863/TAS.2023.05.121.33

Pages: 177-183

Published: 30.05.2023

Abstract: to increase productivity in processing processes, it is important to achieve high material removal rates while maintaining stable cutting modes, which largely depends on the dynamic properties of the machine design. Receptor Coupling Subsystem Analysis (RCSA) is a combined analytical and experimental method used to determine the stability of a machine under various tool configurations. This method uses experimental measurements of the mobility of the holder-spindle assembly in combination with an analytical tool model to predict the dynamics of various combinations of the tool and the holder-spindle. This article proposes an alternative approach using the concept of a tool on an elastic support to predict the dynamics of the machine in various tool configurations. The proposed model includes an elastic support provided by the holder-spindle assembly, which is measured using vibration tests. The model also includes a distributed elastic interface layer between the spindle holder and the tool shank to represent the characteristics of the connection interface. This allows us to present in more detail the flexibility and damping of the joint surface, which play a crucial role in the dynamics of the machine. Experiments have been carried out to demonstrate the effectiveness of the proposed model in predicting the dynamics of milling operations, and it is shown that the model accurately predicts the effect of dynamic damping of the spindle when adjusting the tool.

Key words: machine tool, modeling, analysis.