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    陈东菊, 范晋伟, 雒驼, 张飞虎. Daubechies小波在机床动态误差特征提取与辨识中的应用[J]. 北京工业大学学报, 2012, 38(10): 1467-1473.
    引用本文: 陈东菊, 范晋伟, 雒驼, 张飞虎. Daubechies小波在机床动态误差特征提取与辨识中的应用[J]. 北京工业大学学报, 2012, 38(10): 1467-1473.
    shu
    CHEN Dong-ju, FAN Jin-wei, LUO Tuo, ZHANG Fei-hu. Application of Daubechies Wavelet on Feature Extraction and Identification of Dynamic Error of Machine Tool[J]. Journal of Beijing University of Technology, 2012, 38(10): 1467-1473.
    Citation: CHEN Dong-ju, FAN Jin-wei, LUO Tuo, ZHANG Fei-hu. Application of Daubechies Wavelet on Feature Extraction and Identification of Dynamic Error of Machine Tool[J]. Journal of Beijing University of Technology, 2012, 38(10): 1467-1473.
    shu

    Daubechies小波在机床动态误差特征提取与辨识中的应用

    Application of Daubechies Wavelet on Feature Extraction and Identification of Dynamic Error of Machine Tool

      摘要
    • 摘要: 针对机床各部件的动态信号特征在加工工件的面形误差中提取困难的问题,结合加工工件面形检测结果,提出基于小波变换和功率谱密度分析的超精密机床动态误差特征提取的新方法.采用Daubechies小波变换,从加工检测信号处分解出了低频和高频信号.同时,将小波变换与功率谱密度相结合,实现了机床动态误差特征的有效提取与辨识。

       

      Abstract: A new method for extracting feature of the dynamic error of machine tool from the flatness surface is proposed.The dynamic error is identified based on the character analysis of the test result.By Daubechies wavelet,the information that contains high frequency signal and low frequency signal is decomposed from the flatness error of workpiece surface.At the same time,the wavelet transform and power spectral density analysis are combined,and the dynamic errors of machine tool from the measured flatness error of workpiece are extracted and identified.

       

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