DocumentCode :
2541605
Title :
Incipient Feature extraction based on singular value decomposition and undecimated lifting scheme packet
Author :
Duan Lixiang ; Liu Nan ; Tang Yu ; Liu Yafeng ; Zhang Qinchun
Author_Institution :
Coll. of Mech. & Transp. Eng., China Univ. of Pet. (Beijing), Beijing, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1829
Lastpage :
1833
Abstract :
Vibration signal measured from machinery is often heavily interfered with by various noises. This paper puts forward a joint method to reduce noises, acquire the enhanced signals from the decomposed subbands and extract the incipient fault features. First, the signals are denoised by the method of singular value decomposition (SVD). Then, the denoised signal is decomposed into four layers by undecimated lifting scheme packet (ULSP). Finally, all 16 subbands of the fourth layer are plotted and the rich-fault-information subbands are used to extract incipient features. The effectiveness of the proposed method is validated with simulated data. Furthermore, in the processing of engineering signal, the weak feature caused by the fault of a valve in reciprocating compressor is bulged and the early failure of spring is detected.
Keywords :
compressors; failure analysis; feature extraction; mechanical engineering computing; signal denoising; singular value decomposition; springs (mechanical); valves; vibrations; SVD; ULSP; decomposed subband; engineering signal; incipient fault feature extraction; information subband; machinery; noise reduction; reciprocating compressor; signal denoising; signal enhancement; singular value decomposition; spring failure detection; undecimated lifting scheme packet; valve; vibration signal; Feature extraction; Frequency domain analysis; Valves; Vibrations; Wavelet packets; feature extraction; signal processing; singular value decomposition; undecimated lifting scheme packet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233752
Filename :
6233752
Link To Document :
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