Optics and Precision Engineering, Volume. 31, Issue 19, 2867(2023)
Research process on operation performances of parallel type six-axis acceleration sensing mechanisms
Six-axis acceleration sensing has urgent application demands in the fields of robotics, aerospace, and ultra-precision machining, having become the core technology in the development of cutting-edge high-end equipment. Parallel-type six-axis accelerometers offer the salient advantages of compact structures and high decoupling precisions, and their measurement performance relates to the operation performance of sensing mechanisms. First, from the perspective of working mechanisms, this paper clarifies five differences between parallel-type six-axis acceleration sensing mechanisms, parallel robots, and parallel-type six-axis force sensing mechanisms. From mathematical and mechanical perspectives, it then systematically describes the characterization and optimization methods for operation performance factors, including static stiffness, singularity, fundamental resonance, and fault restoration, and analyzes reasons for the non-adaptive nature of existing methods. Subsequently, the necessity and basic requirements of six-dimensional acceleration calibration platforms are elucidated, and the advantages and disadvantages of four principle schemes are analyzed. Finally, it is concluded that to fully leverage the performance advantages of parallel-type six-axis acceleration sensing mechanisms, it is necessary to further address key technical problems by exploring internal performance relationships, structures, and excitations; reconfiguring geometric and topological structures; and designing and optimizing calibration platforms.
Get Citation
Copy Citation Text
Jingjing YOU, Haofei SHI, Xianzhu ZHANG. Research process on operation performances of parallel type six-axis acceleration sensing mechanisms[J]. Optics and Precision Engineering, 2023, 31(19): 2867
Category:
Received: Feb. 8, 2023
Accepted: --
Published Online: Mar. 18, 2024
The Author Email: YOU Jingjing (youjingjing251010@njfu.edu.cn)