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Motion-force Transmissibility Characteristic Analysis of a Redundantly Actuated and Overconstrained Parallel Machine

  • Hai-Qiang Zhang
  • Hai-Rong FangEmail author
  • Bing-Shan Jiang
Research Article

Abstract

This paper presents a novel 1T2R three degrees of freedom redundantly actuated and overconstrained 2\(\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\rm{P}}\rm{RU}-\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\rm{P}}R\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\rm{P}}S\)S parallel machining head (\(\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\rm{P}}\) denotes the active prismatic joint), which can construct 5-axis hybrid machine to complete high speed freedom surface milling for large complex structural components in aerospace. Firstly, based on the screw theory, the mobility of the proposed parallel manipulator is briefly analysed. Secondly, the kinematic inverse position and the parasitic motion of the parallel manipulator are explicitly expressed. Furthermore, motion-force transmission performance evaluation indices are derived in detail via an alternative approach based on the screw theory. More importantly, a simple method for quickly solving the maximum virtual power coefficient is proposed, and the motion-force transmission performance evaluation index is greatly improved. To evaluate the kinematic performance, its workspace is calculated. With numerical examples, performance distribution atlases of the manipulator are depicted visually. The corresponding results illustrate that the proposed parallel manipulator has better orientation workspace and superior motion-force transmission performance than the 2PRU-PRS parallel manipulator, which proves the validity and applicability of applying this manipulator as a machining head.

Keywords

Redundantly actuated overconstrained parallel manipulator motion-force transmission performance workspace 

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Notes

Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities (Nos. 2018JBZ007, 2018YJS136 and 2017YJS158), China Scholarship Council (CSC) (No. 201807090079), and National Natural Science Foundation of China (NSFC) (No. 51675037).

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Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical, Electronic and Control EngineeringBeijing Jiaotong UniversityBeijingChina

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