• DocumentCode
    2297060
  • Title

    Application of data mining in fault diagnoses For machinery

  • Author

    Han, Yilun ; Ming, Sun

  • Author_Institution
    Inst. of Mechano-Electron. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
  • Volume
    3
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1552
  • Lastpage
    1555
  • Abstract
    Data mining can draw out much useful knowledge and information unknown beforehand from amounts of uncompleted, unstable, random data. The paper studies the application about the technology of data mining based on wavelet theory in fault diagnosis for machinery according to up-to-date outcome, and brings forward the data mining way based on wavelet theory, we do verification by experiment. The wavelet transform can draw out the feature of fault, the neural network based on wavelet can effectively carry out the classification of faults. The basis can be supplied for its application.
  • Keywords
    data mining; fault diagnosis; machinery; mechanical engineering computing; neural nets; wavelet transforms; data mining application; fault diagnosis; machinery; neural network; up-to-date outcome; wavelet theory; wavelet transform; Artificial neural networks; Data mining; Gears; Vibrations; Wavelet analysis; Wavelet packets; mining; neural network; wavelet;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583723
  • Filename
    5583723