Cable Angle and Minimum Resultant Force Response Analysis of Lower Limb Traction Device for Rehabilitation Robot With Interval Parameters

Author:

Li Yuan12,Zi Bin12,Zhou Bin3,Zhao Ping3,Ge Q.J.4

Affiliation:

1. School of Mechanical Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, China;

2. Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, China

3. School of Mechanical Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, China

4. Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY 11794-2300

Abstract

Abstract This paper proposes a hybrid uncertainty analysis method (HUAM) based on the first-order interval perturbation method (FIPM) and Monte Carlo method (MCM) for minimum resultant force response analysis of the lower limb traction device (LLTD) of a hybrid-driven parallel waist rehabilitation robot (HDPWRR) with interval parameters. Based on the analysis of cable angles by using the interval algorithm, the problem of non-uniqueness of the force solution in redundant constraint mechanisms is solved. The force response domain prediction with interval parameters on rehabilitation patients is estimated by using the HUAM which combining the first-order interval perturbation technique with direct Monte Carlo method in different stages, and it reduces the calculation amount. First, the kinematic and static models of the LLTD with deterministic information are established according to its work principle. Then, the interval matrices with interval parameters are calculated by using the FIPM and the response of cable angles is combined with the static model. Third, by numerical examples, the accuracy and efficiency of the HUAM for solving the force response domain problem with interval parameters are verified. The bounds of cable angle response domain of the interval LLTD model are determined. Finally, the minimum resultant force response domain prediction with interval parameters on rehabilitation patients is estimated by combining the FIPM and MCM.

Funder

National Natural Science Foundation of China

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications,Software

Reference31 articles.

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