【摘要】 为提高中子衍射谱仪在残余应力测量过程中的样品定位精度,考虑样品台热误差对定位精度的影响,提出了样品台热误差的稳健RBF建模方法。首先通过热结构有限元仿真分析了样品台温度场及热变形的特点;然后根据样品台运动位置、测量点位置、测温点温度变化和测量点热变形的有限元仿真数据,建立了未训练的RBF网络模型;针对建模所用温度数据中存在干扰的问题,在网络训练中以稳健损失函数为目标函数,采用梯度下降法调节隐节点的宽度和权值,最终建立了样品台热误差稳健RBF解析预测模型。仿真结果表明,该建模方法可减少训练样本中温度数据受干扰的影响,提高模型的稳健性,能准确地预测样品台热误差,预测精度小于3μm。更多还原

【Abstract】 In order to improve the accuracy of the sample localization in the residual stress measurement of the neutron diffraction spectrometer,the influence of the sample stage thermal error on the positioning accuracy was considered,and a robust RBF modeling method is proposed. Firstly,the characteristics of the temperature field and thermal deformation were analyzed by finite element simulation. Then,an unsupervised RBF model was established based on the simulation data of the stage movement position,the measurement point position,the temperature change and the measured point thermal deformation. In order to solve the problem of interference in temperature data,the robustness loss function was used as the objective function in the network training,and the width and weight of the hidden nodes were adjusted by the gradient descent method. Finally,the robust RBF thermal error prediction model was established. The simulation results show that the modeling method can reduce the influence of interference and predict the thermal error of the sample stage accurately. The prediction accuracy was less than 3 μm.更多还原