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Developmental and Experimental Study on a Double-Excitation Ultrasonic Elliptical Vibration-Assisted Cutting Device.

Authors :
Hu, Gaofeng
Xin, Wendong
Zhang, Min
Lu, Junti
Lu, Yanjie
Zhou, Shengming
Zheng, Kai
Source :
Machines; Jun2024, Vol. 12 Issue 6, p379, 15p
Publication Year :
2024

Abstract

Ultrasonic elliptical vibration-assisted cutting (UEVC) has been successfully applied in the precision and ultra-precision machining of hard and brittle materials due to its advantages of a low cutting force and minimal tool wear. This study developed a novel double-excitation ultrasonic elliptic vibration-assisted cutting (D-UEVC) device by coupling ultrasonic vibrations in orthogonal dual paths. A two-degree-of-freedom vibration system of the D-UEVC was modeled, form which the elliptical trajectory of the end under different phase angle φ values was derived. The initial dimensions of the D-UEVC device were obtained through theoretical calculations. Subsequently, with the aid of finite element analysis methods, structural dynamic analysis of the device was conducted to obtain the elliptical vibration trajectory under different phase differences of the excitation source. In order to verify the cutting trajectory and cutting performance of the D-UEVC device, a prototype of the device was developed, and a series of vibration performance tests as well as the Inconel 718 cutting experiment were conducted. The experimental results illustrated that the D-UEVC device can achieve the elliptical vibration trajectory at the tool tip with a resonant frequency of 36.5 KHz. The adjustable elliptical vibration trajectories covered a range of ±4 μm in the axial and radial directions. Compared with the surface roughness Ra = 0.36 μm under the conventional cutting, the surface roughness of Inconel 718 under D-UEVC was Ra = 0.215 μm. Thus, the surface quality can be significant improved by utilizing the D-UEVC device. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20751702
Volume :
12
Issue :
6
Database :
Complementary Index
Journal :
Machines
Publication Type :
Academic Journal
Accession number :
178187221
Full Text :
https://doi.org/10.3390/machines12060379