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双层预紧式6维力传感器预紧力对精度影响分析

王志军 侯雨雷 姚建涛 叶冬 赵永生

机器人2012,Vol.34Issue(4):393-398,6.
机器人2012,Vol.34Issue(4):393-398,6.DOI:10.3724/SP.J.1218.2012.00393

双层预紧式6维力传感器预紧力对精度影响分析

Influence of the Pre-tightening Force on Accuracy of the Double-layer Pre-stressed Six-axis Force Sensor

王志军 1侯雨雷 1姚建涛 1叶冬 1赵永生1

作者信息

  • 1. 燕山大学,河北秦皇岛066004
  • 折叠

摘要

Abstract

For the disadvantages of the six-axis force sensor based on the classical Stewart structure, a double-layer pre-stressed six-axis force sensor is designed and manufactured, and accuracy analysis and experimental research are carried out. Firstly, structure characteristics of the six-axis force sensor are introduced. The mathematical model of the sensor and the representation of the pre-tightening force are established by using screw theory. In order to improve the measurement accuracy, a method for reducing the error of the prc-tightening branch's structural deformation by increasing the pre-tightening force is proposed on the basis of analyzing the structure of pre-tightening branch. Secondly, the structural deformation of pre-tightening branch under different pre-tightening forces is simulated by FEM (finite element method). Finally, the sensor prototype is manufactured and the calibration system is developed. The calibration experiment is performed under different pre-tightening forces. It is shown that the maximum Error I and Error II are reduced from 2.73%, 2.43% to 0.41%, 0.64% of the full scales respectively by increasing the pre-tightening force. The experiment results indicate that the error caused by the pie-tightening branch's structural deformation is reduced effectively and the measuring accuracy of the sensor is improved by increasing the pre-tightening force, which verifies the correctness of the theoretical analysis and simulation.

关键词

6维力传感器/双层预紧/预紧力/结构变形/精度

Key words

six-axis force sensor/ double-layer pre-stressed/ pre-tightening force/ structural deformation/ accuracy

分类

信息技术与安全科学

引用本文复制引用

王志军,侯雨雷,姚建涛,叶冬,赵永生..双层预紧式6维力传感器预紧力对精度影响分析[J].机器人,2012,34(4):393-398,6.

基金项目

国家自然科学基金资助项目(50975245) (50975245)

河北省自然科学基金资助项目(E2011203184) (E2011203184)

秦皇岛市科学技术研究与发展计划资助项目(201001A103). (201001A103)

机器人

OA北大核心CSCDCSTPCD

1002-0446

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