• DocumentCode
    1898825
  • Title

    Extraction Fault Rule of Rotation Equipment Based on Rough Set

  • Author

    Li Meng ; Shu Yunxing ; Mao Jiandong ; Li Xiaohua

  • Author_Institution
    Luoyang Inst. of Sci. & Technol., Luoyang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    604
  • Lastpage
    607
  • Abstract
    In order to improve the accuracy of rotation equipment fault diagnosis, and be directed to the mechanical failure in the UCI database, the characteristics of detection parameter in the data set is analysed, no filter vertical amplitude, filter vertical vibration speed, and the key detection parameter of the rotating equipment failure is vibration frequency. As a result, the method which the data of rotation equipment failure is mined by rough set is proposed. In the data set, the data selection, discrete, establishment of decision-making table and reduction method are introduced. Expert system rule base of rotating equipment failure will be realized by extraction of rotating equipment fault rule.
  • Keywords
    failure (mechanical); fault diagnosis; machinery; mechanical engineering computing; rough set theory; data selection; extraction fault rule; mechanical failure; reduction method; rotation equipment fault diagnosis; rough set; vibration frequency; Data analysis; Data mining; Databases; Equipment failure; Failure analysis; Fault detection; Fault diagnosis; Filters; Frequency; Vibrations; fault rule; rotation equipmen; rought set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.380
  • Filename
    5287754