Application of Daubechies wavelet on feature extraction and identification of dynamic error of machine tool

Dong Ju Chen; Jin Wei Fan; Tuo Luo; Fei Hu Zhang

Application of Daubechies wavelet on feature extraction and identification of dynamic error of machine tool

Dong Ju Chen^*
, Jin Wei Fan
, Tuo Luo
, Fei Hu Zhang

^*Corresponding author for this work

Beijing University of Technology
School of Mechatronics Engineering, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

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.

Original language	English
Pages (from-to)	1467-1473
Number of pages	7
Journal	Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology
Volume	38
Issue number	10
State	Published - Oct 2012
Externally published	Yes

Keywords

Error identification
Feature extraction
Power spectral density
Ultra-precision machine
Wavelet analysis

Cite this

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title = "Application of Daubechies wavelet on feature extraction and identification of dynamic error of machine tool",

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.",

keywords = "Error identification, Feature extraction, Power spectral density, Ultra-precision machine, Wavelet analysis",

author = "Chen, \{Dong Ju\} and Fan, \{Jin Wei\} and Tuo Luo and Zhang, \{Fei Hu\}",

year = "2012",

month = oct,

language = "英语",

volume = "38",

pages = "1467--1473",

journal = "Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology",

issn = "0254-0037",

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T1 - Application of Daubechies wavelet on feature extraction and identification of dynamic error of machine tool

AU - Chen, Dong Ju

AU - Fan, Jin Wei

AU - Luo, Tuo

AU - Zhang, Fei Hu

PY - 2012/10

Y1 - 2012/10

N2 - 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.

AB - 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.

KW - Error identification

KW - Feature extraction

KW - Power spectral density

KW - Ultra-precision machine

KW - Wavelet analysis

UR - https://www.scopus.com/pages/publications/84868631698

M3 - 文章

AN - SCOPUS:84868631698

SN - 0254-0037

VL - 38

SP - 1467

EP - 1473

JO - Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology

JF - Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology

IS - 10

ER -

Application of Daubechies wavelet on feature extraction and identification of dynamic error of machine tool

Abstract

Keywords

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