DocumentCode :
2809782
Title :
Feature extraction of turbine abnormal vibration condition based on ICA
Author :
An, Hongwen ; Liu, Yibing ; Zhou, Yanbing ; Yang, Huan
Author_Institution :
Key Lab. of Condition Monitoring & Control for Power Plant Equip., North China Electr. Power Univ., Beijing, China
fYear :
2011
fDate :
15-17 July 2011
Firstpage :
4080
Lastpage :
4083
Abstract :
Independent component analysis of a single measured mixing signal, that is single channel Independent component analysis (SCICA), has been widely used in feature extraction of a signal. In this paper we provide a example of using single channel ICA for extracting the feature of a abnormal running condition of a turbine from measured vibration signals, in order to show the effect of SCICA. The bearing vibration signals of the turbine are measured under two different running conditions. We choose one bearing vibration signal with clear abnormal information to test. The results show that the basic functions of SCICA have different characters for different turbine running condition and can be used as features. The results need further analyze to distinguish the different states.
Keywords :
condition monitoring; feature extraction; independent component analysis; mechanical engineering computing; turbines; vibrations; SCICA; abnormal running condition; abnormal vibration condition; bearing vibration signals; feature extraction; single channel independent component analysis; turbines; Condition monitoring; Fault diagnosis; Feature extraction; Independent component analysis; Turbines; Vibration measurement; Vibrations; Feature Extraction; Single Channel Independent Component Analysis; Turbine; Vibration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
Conference_Location :
Hohhot
Print_ISBN :
978-1-4244-9436-1
Type :
conf
DOI :
10.1109/MACE.2011.5987899
Filename :
5987899
Link To Document :
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