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基于MEA-NARX神经网络主轴热误差建模
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Modeling of Spindle Thermal Error Based on MEA-NARX Neural Network
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    摘要:

    为了有效提高基于非线性时间序列的热误差预测模型精度,利用F统计检验确定模糊C均值聚类的聚类数目,结合不同量纲一化处理的灰色关联分析排序筛选出关键温度测点,建立基于NARX神经网络的热误差预测模型,通过设置输入延时阶数、输出延时阶数和隐含层神经元个数的范围,利用思维进化算法对输入、输出延时阶数和隐含层神经元个数进行寻优,与随机选取参数的NARX神经网络预测模型相比,模型预测精度提高了36.98%。

    Abstract:

    In order to effectively improve the accuracy of the thermal error prediction model based on nonlinear time series, the cluster number of fuzzy C mean clustering was determined by statistical test, and the key temperature measurement points were sorted and selected by combining the grey correlation analysis with different dimensionless processing. The thermal error prediction model based on NARX neural network was established; by setting the ranges of the input delay order, output delay order and the number of hidden neurons, the mind evolutionary algorithm was used to optimize the input and output delay order and the number of hidden neurons. Compared with the NARX neural network prediction model with randomly selected parameters, the prediction accuracy of the model is improved by 36.98%.

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孙昂,王丽爽,谢新连.基于MEA-NARX神经网络主轴热误差建模[J].机床与液压,2022,50(24):49-53.
SUN Ang, WANG Lishuang, XIE Xinlian. Modeling of Spindle Thermal Error Based on MEA-NARX Neural Network[J]. Machine Tool & Hydraulics,2022,50(24):49-53

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  • 在线发布日期: 2023-01-12
  • 出版日期: 2022-12-28