LAPSE:2023.1072
Published Article
LAPSE:2023.1072
Synthesis of 2-DOF Decoupled Rotation Stage with FEA-Based Neural Network
February 21, 2023
Abstract
Transfer printing technology has developed rapidly in the last decades, offering a potential demand for 2-DOF rotation stages. In order to remove decoupling modeling, improve motion accuracy, and simplify the control method, the 2-DOF decoupled rotation stages based on compliant mechanisms present notable merits. Therefore, a novel 2-DOF decoupled rotation stage is synthesized of which the critical components of decoupling are the topological arrangement and a novel decoupled compound joint. To fully consider the undesired deformation of rigid segments, an FEA-based neural network model is utilized to predict the rotation strokes and corresponding coupling ratios, and optimize the structural parameters. Then, FEA simulations are conducted to investigate the static and dynamic performances of the proposed 2-DOF decoupled rotation stage. The results show larger rotation strokes of 4.302 mrad in one-axis actuation with a 1.697% coupling ratio, and 4.184 and 4.151 mrad in two-axis actuation with undesired Rz rotation of 0.014 mrad with fewer actuators than other works. In addition, the first natural frequency of 2151 Hz is also higher, enabling a wider working frequency range.
Keywords
2-DOF rotation stage, compliant mechanisms, micro manipulation, transfer printing
Suggested Citation
Ye T, Li Y. Synthesis of 2-DOF Decoupled Rotation Stage with FEA-Based Neural Network. (2023). LAPSE:2023.1072
Author Affiliations
Ye T: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China [ORCID]
Li Y: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China [ORCID]
Journal Name
Processes
Volume
11
Issue
1
First Page
192
Year
2023
Publication Date
2023-01-06
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11010192, Publication Type: Journal Article
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LAPSE:2023.1072
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https://doi.org/10.3390/pr11010192
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Feb 21, 2023
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CC BY 4.0
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