DocumentCode :
533248
Title :
A novel method for feature extraction of rotating machinery vibration signals
Author :
Fang, Li-Cheng ; Li, Shun-Ming ; Shen, Huan ; Zhang, Yuan-Yuan ; Du, Jian-Jian
Author_Institution :
Coll. of Energy & Power Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Volume :
11
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
A novel method named correlation of time series and squaring for suppressing the noise in the feature extraction was developed. It eliminates the impact of zero-average noise and non-stationary variance intrusion colored noise in sampling series, gets over the difficulty of frequency identification because of strong background noise in the subsequence analysis, protrudes the feature components of original signals, and provides a wonderful former data for spectrum analysis using the multi-correlation of time series. The results of simulation analysis to extract the feature of some engine´s rotating shaft vibration signals validate that this method can be used to extract the features of vibration signals of rotating machinery. They also prove this method has bright future in the engineering applications.
Keywords :
feature extraction; mechanical engineering computing; shafts; spectral analysis; time series; turbomachinery; vibrations; engine rotating shaft vibration signals; feature extraction method; frequency identification; noise suppression; nonstationary variance intrusion colored noise; rotating machinery vibration signals; spectrum analysis; time series correlation method; zero-average noise; Correlation; Engines; Feature extraction; Noise; Noise reduction; Rotors; Vibrations; feature extraction; rotating machinery; self-correlation; time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623243
Filename :
5623243
Link To Document :
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