Daubechies小波在机床动态误差特征提取与辨识中的应用

摘要

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.%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。