• DocumentCode
    2154647
  • Title

    Research on key techniques for intelligent prediction of fault in safe running of complex electromechanical equipment

  • Author

    Xiaoli, Xu ; Bin, Ren

  • Author_Institution
    School of Mechanical Engineering, Beijing Institute of Technology, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The intelligent prediction of fault is an important and difficult modern technique in our world, and the Technique can assure the safe running of key equipment and improve the working condition of it. The Technique is mainly based on large and complex electromechanical equipment, research and disclosure the new methods and technique on intelligent prediction of fault based on data mining. Through the characteristic of fault data of electromechanical system, the acquisition methods of fault prediction based on data mining will be found out; the flow of fault prediction based on data mining will be set up; the fault prediction system and relative engineering application software will be made based on data mining. The test shows: the key technique for intelligent prediction of fault in safe running of complex electromechanical equipment can improve the efficiency of fault prediction for large electromechanical equipment.
  • Keywords
    Artificial neural networks; Classification algorithms; Data mining; Fault diagnosis; Instruments; Maintenance engineering; Vibrations; data mining; electromechanical equipment; intelligent prediction of fault;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5691510
  • Filename
    5691510