Condition Feature Extraction of Machine Tools Based on Wavelet Packet Energy Spectrum Analysis and Bispectrum Analysis of Current Signal

Abstract:

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Based on the study of the characteristics of load current signal, this article develops a method to extract features that can be use to distinguish the different working status of machine tools in real-time manner. The features are extracted from wavelet packet energy spectrum and bispectrum of the load current signal, and thus can take advantages of both wavelet packet transforms and bispectrum in signal analysis. Experimental results show that, compared with the features extracted from wavelet packet energy spectrum or bispectrum alone, the features extracted by applying the proposed method can provide better performance in term of identifying the machine working status.

Info:

Periodical:

Edited by:

Di Zheng, Yiqiang Wang, Yi-Min Deng, Aibing Yu and Weihua Li

Pages:

847-850

DOI:

10.4028/www.scientific.net/AMM.101-102.847

Citation:

T. F. Fang and G. F. Li, "Condition Feature Extraction of Machine Tools Based on Wavelet Packet Energy Spectrum Analysis and Bispectrum Analysis of Current Signal", Applied Mechanics and Materials, Vols. 101-102, pp. 847-850, 2012

Online since:

September 2011

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Price:

$35.00

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