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Kinematic analysis and multi-objective optimization of a new reconfigurable parallel mechanism with high stiffness

Published online by Cambridge University Press:  30 May 2017

Guanyu Huang
Affiliation:
Department of Mechanical Engineering, Beijing Jiaotong University, Beijing, 100044, P.R. China E-mails: [email protected], [email protected], [email protected], [email protected]
Sheng Guo
Affiliation:
Department of Mechanical Engineering, Beijing Jiaotong University, Beijing, 100044, P.R. China E-mails: [email protected], [email protected], [email protected], [email protected]
Dan Zhang*
Affiliation:
Department of Mechanical Engineering, Beijing Jiaotong University, Beijing, 100044, P.R. China E-mails: [email protected], [email protected], [email protected], [email protected]
Haibo Qu
Affiliation:
Department of Mechanical Engineering, Beijing Jiaotong University, Beijing, 100044, P.R. China E-mails: [email protected], [email protected], [email protected], [email protected]
Hongyan Tang
Affiliation:
Department of Mechanical Engineering, Beijing Jiaotong University, Beijing, 100044, P.R. China E-mails: [email protected], [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

This paper presents a novel reconfigurable parallel mechanism, which can serve as a machine tool. The proposed parallel mechanism can change its structure parameters by driving a bevel gear system fixed in the base platform. First, the forward and inverse kinematics of the proposed mechanism are investigated. Second, the reachable workspace and Jacobian matrix are conducted. Based on the Jacobian matrix, the stiffness model and dexterity of the end effector are developed in detail. Finally, a multi-objective optimization is performed by using the Genetic Algorithm, and the workspace and global performance indexes of stiffness as well as the dexterity are considered as the performance indices to improve the performance of the reconfigurable parallel mechanism. Finally, Pareto frontier figure and several tables are provided to illustrate the results of the optimization. The results showed the proposed method has improved the performance of the reconfigurable machine tool in terms of its stiffness and dexterity.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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