Title of article
An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction
Author/Authors
Chen, Dongju College of Mechanical Engineering & Applied Electronics Technology - Beijing University of Technology, China , Zhou, Shuai College of Mechanical Engineering & Applied Electronics Technology - Beijing University of Technology, China , Dong, Lihua College of Mechanical Engineering & Applied Electronics Technology - Beijing University of Technology, China , Fan, Jinwei College of Mechanical Engineering & Applied Electronics Technology - Beijing University of Technology, China
Pages
11
From page
1
To page
11
Abstract
This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.
Keywords
Time-Frequency Feature Extraction , Machine Tools , Error Source Identification
Journal title
Shock and Vibration
Serial Year
2016
Full Text URL
Record number
2617943
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