• 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