帧(网络)
校准
联轴节(管道)
拓扑(电路)
人工智能
物理
计算机科学
数学
组合数学
机械工程
工程类
量子力学
电信
作者
Yu-Jen Wang,Ching-Wei Hsu,Chung-Yang Sue
出处
期刊:IEEE Sensors Journal
[Institute of Electrical and Electronics Engineers]
日期:2020-06-11
卷期号:20 (20): 12134-12145
被引量:27
标识
DOI:10.1109/jsen.2020.2999156
摘要
In this study, a dual-frame six-axis force and torque (F/T) sensor is proposed. The dual-frame F/T sensor consists of inner and outer elastic parts for simultaneously measuring F x , F y , and T z as well as T x , T y , and F z . Load-strain equations were derived according to beam theory and structure theory. These equations and optimization methods were used to establish the parameter design process of the F/T sensor. A calibration machine is proposed to generate a large number of multiaxis training and testing F/T sets for sensor calibration. The calibration results from the least square method and neural network (NN) model revealed the coupling and nonlinearity of the multiaxis F/T sensor. The dual-frame structure reduced the coupling effect between the inner-frame and outer-frame measuring F/Ts. Therefore, the calibration process could be simplified using two tri-axis F/T sets with NN models. The calibration process was verified using six-axis testing F/T sets, and a mean calibration error of 0.25% was observed.
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