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Research on static decoupling algorithm for piezoelectric six axis force/torque sensor based on LSSVR fusion algorithm

机译:基于LSSVR融合算法的压电六轴力/力矩传感器静态解耦算法研究

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Six axis force/torque sensors with characteristics of high precision, high reliability, and high dynamic, have become one of the major bottlenecks restricting the development of the robot. Aiming at the existing decoupling problem of piezoelectric six axis force/torque sensor with four point support structure, this paper presents the research and application on static decoupling method. Firstly, initial experimental data for decoupling of piezoelectric six axis force/torque sensor is obtained by making a calibration experiment. And then, experimental data are analyzed according to evaluate indicator. The linear decoupling algorithm based on the least square (LS) method is performed. Fusion decoupling algorithm based on Least Square Support Vector Machine Regression (LSSVR) is adopted to optimize multi-dimensional nonlinear characteristics of sensor output. The mapping relation between input and output of the sensor is identified. After LSSVM fusion algorithm decoupling, the maximum nonlinear error and cross coupling error are 0.89%, and 0.1%, respectively. The results show that the decoupling of LSSVR fusion algorithm can reduce the nonlinear error and cross coupling error of the fabricated piezoelectric six axis force/torque sensor. It has important significance to improve the measurement accuracy of robot force feedback with piezoelectric six axis force/torque sensors.
机译:具有高精度,高可靠性和高动态特性的六轴力/扭矩传感器已经成为制约机器人发展的主要瓶颈之一。针对具有四点支撑结构的压电六轴力/力矩传感器存在的解耦问题,提出了静态解耦方法的研究与应用。首先,通过进行校准实验,获得了用于压电六轴力/转矩传感器去耦的初始实验数据。然后根据评价指标对实验数据进行分析。执行基于最小二乘(LS)方法的线性去耦算法。采用基于最小二乘支持向量机回归(LSSVR)的融合解耦算法,优化传感器输出的多维非线性特征。识别传感器的输入和输出之间的映射关系。 LSSVM融合算法解耦后,最大非线性误差和交叉耦合误差分别为0.89%和0.1%。结果表明,LSSVR融合算法的解耦可以减小所制造的压电六轴力/转矩传感器的非线性误差和交叉耦合误差。对于利用压电六轴力/转矩传感器提高机器人力反馈的测量精度具有重要意义。

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