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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.
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SHOCK AND VIBRATION
ISSN: 1070-9622
Year: 2016
Volume: 2016
1 . 6 0 0
JCR@2022
ESI Discipline: ENGINEERING;
ESI HC Threshold:166
CAS Journal Grade:4
Cited Count:
WoS CC Cited Count: 6
SCOPUS Cited Count: 4
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 0