A heavy load miniature six-component force sensing mechanism with hybrid branches

Structure drawing of the proposed heavy load miniature six-component force sensing mechanism with hybrid branches. [Display omitted] •A heavy load miniature force sensing mechanism with hybrid branches is proposed.•The stiffness model and force mapping relationship of the mechanism are constructed.•...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2020-06, Vol.157, p.107623, Article 107623
Hauptverfasser: Yao, Jiantao, Zu, Lizheng, Ruan, Haoqi, Cai, Dajun, Xu, Yundou, Zhao, Yongsheng
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Sprache:eng
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Zusammenfassung:Structure drawing of the proposed heavy load miniature six-component force sensing mechanism with hybrid branches. [Display omitted] •A heavy load miniature force sensing mechanism with hybrid branches is proposed.•The stiffness model and force mapping relationship of the mechanism are constructed.•The maximum nonlinear error in each direction of the mechanism prototype is 1.65%. The heavy-load force sensing mechanisms with small size and wide range have always been a challenge. To tackle this challenge, we propose a parallel six-component force sensing mechanism with sensitive measuring branches and high load-bearing branches based on the design idea of hybrid branch. Based on the virtual work principle and the geometric compatibility condition, the stiffness model and force mapping relationship of the mechanism are deduced, which provide the theoretical basis for the mechanism. Further, the comparison between the numerical calculation and the simulation values of the force sensing mechanism shows that the mathematical model is in good agreement with the finite element model. Finally, a calibration testing platform is built to analyze the measuring performances of the force sensing mechanism. By using the least square method to analyze the experimental data, the calibration matrix is obtained and the maximum nonlinear error is 1.65%.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2020.107623