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Calibration of the Hall Measurement System for a 6-DOF Precision Stage Using Self-Adaptive Hybrid TLBO

机译:使用自适应混合TLBO校准6自由度精密平台的霍尔测量系统

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摘要

To determine the planar motion of a 6-DOF precision stage, a measurement system based on three Hall sensors is adopted to obtain the X, Y, Rz motions of the stage. The machining and assembly errors in the actual mechanical system, which are difficult to measure directly, cause the parameters in the model of the Hall measurement system to deviate from their designed values. Additionally, the vertical movement of the stage will render the measurement model nonlinear. To guarantee the accuracy of the measurement, the parameters in the measurement model should be estimated and the nonlinearity compensated. In this paper, a novel approach based on self-adaptive hybrid TLBO (teaching-learning-based-optimization) is proposed to estimate the parameters in the Hall measurement model. The influences of zero deviations and vertical movements on the measurement accuracy are analyzed and compensated. The effectiveness of the proposed method is validated by experimental results obtained on a 6-DOF precision stage. Thanks to parameter estimation and calibration, the measurement error of the Hall sensor array is reduced to 6 micrometers.
机译:为了确定6-DOF精密平台的平面运动,采用了基于三个霍尔传感器的测量系统来获得平台的X,Y,Rz运动。实际机械系统中的机械和装配误差很难直接测量,因此会导致霍尔测量系统模型中的参数偏离其设计值。此外,平台的垂直移动将使测量模型非线性。为了保证测量的准确性,应估计测量模型中的参数并补偿非线性。本文提出了一种基于自适应混合TLBO(基于教学学习的优化)的新方法来估计霍尔测量模型中的参数。分析并补偿了零偏差和垂直运动对测量精度的影响。通过在6自由度精密平台上获得的实验结果验证了该方法的有效性。由于参数估计和校准,霍尔传感器阵列的测量误差降低到6微米。

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