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

作　　者：陈东菊[1] 范晋伟[1] 雒驼[1] 张飞虎[2] 

机构地区：[1]北京工业大学机械工程与应用电子技术学院,北京100124 [2]哈尔滨工业大学机电工程学院,哈尔滨150001

出　　处：《北京工业大学学报》2012年第10期1467-1473,共7页Journal of Beijing University of Technology

基　　金：国家自然科学基金资助项目(51105005);北京工业大学博士科研启动基金项目(X0001011201101)

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。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.

关 键 词：超精密机床 误差辨识 特征提取 小波分析 功率谱密度 

分 类 号：TH161[机械工程—机械制造及自动化]