- The paper proposes a detailed parametric stiffness analysis of the Orthoglide PKM using flexible-link lumped parameter models and symbolic computation.
- The analysis identified specific geometric design parameters, such as joint angles, as critical influences on both translational and rotational stiffness characteristics.
- Understanding these parametric influences is vital for optimizing the design of high-speed machining parallel manipulators like the Orthoglide for enhanced performance.
Parametric Stiffness Analysis of the Orthoglide
This paper provides a detailed parametric stiffness analysis of the Orthoglide, which is a 3-degree-of-freedom (DOF) translational Parallel Kinematic Machine (PKM). The primary focus is on understanding how the geometric design parameters influence the stiffness characteristics of this mechanism.
Stiffness Modeling Approach
The authors apply a method for modeling the compliance of the Orthoglide based on flexible-link lumped parameter models, effectively addressing the limitations of previous kinetostatic stiffness mapping methods. This approach replaces the compliance across links by localized virtual compliant joints combined with rigid links, allowing for a comprehensive symbolic computation of the stiffness matrix.
Analysis and Results
The Orthoglide's stiffness matrix was computed symbolically allowing for an analytical inspection of design parameters on matrix elements. The research particularly highlights the symbolic computation made possible by the compliant modeling which identified critical design parameters influencing stiffness. The isotropic condition within the Orthoglide's workspace offers a simplified perspective for evaluating stiffness properties.
Numerical tests indicate significant parameters affecting both translational and rotational stiffness. A crucial observation is that the translational stiffness could potentially be enhanced by optimizing the geometric parameters such as the angle between the foot and the actuated joint axis.
Implications and Future Work
Understanding these influences is particularly pertinent for the design optimization of parallel manipulators like the Orthoglide, which are intended for high-speed machining applications. This research demonstrates the utility of symbolic expression in providing intuitive and comprehensive stiffness insights. The ongoing comparison with finite element models and stiffness tests will further validate these findings and refine existing models.
In the broader context of PKM development, the insights from this paper are likely to influence design guidelines, emphasizing the importance of stiffness-oriented optimization to enhance machinability. This work lays a foundation for future exploration into more complex manipulator designs and optimizations driven by stiffness considerations.