Study on axial vibration suppression of ball screws based on acoustic black hole dampers
As one of the key components of machine tools, the dynamic characteristics of the ball screw feed system significantly affect machining accuracy and efficiency. In this paper, the acoustic black hole (ABH) concept is employed to effectively suppress the axial vibration of the ball screw feed system. An additional acoustic black hole (AABH) damper is designed to suppress low-frequency vibrations. To further enhance broadband vibration reduction performance, eccentric acoustic black hole (EABH) and slotted acoustic black hole (SABH) dampers are designed. Harmonic response analysis is performed, and the structural parameters are optimized using the finite element method (FEM). The coupling coefficients between the three types of ABH dampers and the ball screw feed system are calculated The vibration suppression effects of these dampers are validated experimentally. By comparing the amplitude level curve of the system with or without the installation of the ABH dampers, the results show that the maximum amplitude level decreases by 14.06, 27.02, and 23.73 dB, respectively. It is indicated that the three types of ABH dampers designed in this study effectively suppress axial vibration of the ball screw feed system over a wide frequency range, thereby improving the machining accuracy and efficiency of the machine tool.
Authors
- Xiangsheng Gao (ORCID: https://orcid.org/0000-0001-5947-5826)
- Tao Zan (ORCID: https://orcid.org/0000-0001-6263-9553)
- Peng Gao (ORCID: https://orcid.org/0000-0002-1003-3370)
- Tiewei Sun (ORCID: https://orcid.org/0000-0002-1278-0425)
- Min Wang (ORCID: https://orcid.org/0000-0002-9072-8331)
- Yang Yang (ORCID: https://orcid.org/0000-0002-2731-8014)
- Xingxing Yu
Institutions
- Beijing University of Technology (CN)
Publication Details
- Journal
- Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1177/09544062251339052
- Citations
- 1
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- National Natural Science Foundation of China