Extraction Feature of Spindle Unbalance of Machine Tool Based on the Wavelet Transform

Dong Ju Chen; Jin Wei Fan; Fei Hu Zhang

doi:10.4028/www.scientific.net/AMR.279.313

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 279Extraction Feature of Spindle Unbalance of Machine...

Extraction Feature of Spindle Unbalance of Machine Tool Based on the Wavelet Transform

Abstract:

A new method for extracting spectrum feature of spindle unbalance of machine tool is proposed. The flatness error of workpiece surface includes much errors information, and the information contains high frequency signal and low frequency signal. For these errors information, a new identification method of turning errors of workpiece based on the wavelet transform and power spectral density analysis is proposed. According to the focal variation character of wavelet and the energy value of power spectral density analysis, the feature of spindle unbalance from the measured flatness error of workpiece is extracted and identified.

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Periodical:

Advanced Materials Research (Volume 279)

Pages:

313-317

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.279.313

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Online since:

July 2011

Authors:

Dong Ju Chen, Jin Wei Fan, Fei Hu Zhang

Keywords:

Feature Extraction, Flatness Error, Power Spectral Density (PSD), Spindle Unbalance, Wavelet Transform (WT)

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