Fault Feature Extraction by Using Adaptive Chirplet Transform

Author

Guo, Qianjin ; Yu, Haibin ; Hu, Jingtao

Author_Institution

Dept. of Control Eng. & Commun. Syst., Graduate Sch. of Chinese Acad. of Sci., Beijing

Volume

2

fYear

0

fDate

0-0 0

Firstpage

5643

Lastpage

5647

Abstract

The vibration generated by industrial machines always contains nonlinear and nonstationary signals. It is expected that a desired time-frequency analysis method should have good computation efficiency, and have good resolution in both time domain and frequency domain. In this paper, the adaptive Gaussian chirplet distribution for an integrated time-frequency signature extraction of the machine vibration is presented. The adaptive Gaussian chirplet spectrogram is nonnegative, has a high time-frequency resolution, and is free of cross term interference, so it offers the advantage of good localization of the vibration signal energy in the time-frequency domain. Experimental results show that the proposed method is very effective

Keywords

Gaussian distribution; fault diagnosis; time-frequency analysis; transforms; vibration control; adaptive Gaussian chirplet distribution; adaptive Gaussian chirplet spectrogram; adaptive chirplet transform; cross term interference; fault feature extraction; machine vibration signal energy; nonlinear signal; nonstationary signal; time-frequency analysis; time-frequency resolution; time-frequency signature extraction; Chirp; Energy resolution; Feature extraction; Frequency domain analysis; Interference; Signal generators; Signal resolution; Spectrogram; Time domain analysis; Time frequency analysis; Adaptive chirplet transform; Fault detection; Feature Extraction; Time-frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1714155

Filename

1714155