Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146872
Title: A decoupled 6-dof compliant parallel mechanism with optimized dynamic characteristics using cellular structure
Authors: Pham, Minh Tuan
Yeo, Song Huat
Teo, Tat Joo
Wang, Pan
Nai, Sharon Mui Ling
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: Pham, M. T., Yeo, S. H., Teo, T. J., Wang, P. & Nai, S. M. L. (2021). A decoupled 6-dof compliant parallel mechanism with optimized dynamic characteristics using cellular structure. Machines, 9(1). https://dx.doi.org/10.3390/machines9010005
Journal: Machines
Abstract: This paper presents a novel six degrees-of-freedom (DOF) compliant parallel mechanism (CPM) with decoupled output motions, large workspace of ≥6 mm for translations and ≥12◦ for rotations, optimized stiffness, and dynamic properties. The working range and the motion decoupling capability of the six-DOF CPM are experimentally verified, and the mechanical properties are shown to be predictable. The proposed CPM is synthesized by applying the beam-based structural optimization method together with the criteria for achieving motion decoupling capability. In order to improve the dynamic behaviors for the CPM, cellular structure is used to design its end effector. The obtained results show that the dynamic performance of the CPM with cellular end effector is significantly enhanced with the increase of 33% of the first resonance frequency as compared to the initial design. Performances of the three-dimensional (3D)-printed prototype are experimentally evaluated in terms of mechanical characteristics and decoupled motions. The obtained results show that the actual stiffness and dynamic properties agree with the predictions with the highest deviation of ~10.5%. The motion decoupling capability of the CPM is also demonstrated since almost input energy (>99.5%) generates the desired output motions while the energy causes parasitic motions is only minor (<0.5%).
URI: https://hdl.handle.net/10356/146872
ISSN: 2075-1702
DOI: 10.3390/machines9010005
Rights: © 2021 The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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