• DocumentCode
    478199
  • Title

    Self-Organizing Map-Based Fault Dictionary Application Research on Rolling Bearing Faults

  • Author

    Pi, Jun ; Lin, Jiaquan ; Li, Xiangjiang

  • Author_Institution
    Aeronaut. Mech. Coll., Civil Aviation Univ. of China, Tianjin
  • Volume
    3
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    311
  • Lastpage
    315
  • Abstract
    Vibration signal resulting from rolling bearing defects presents a rich content of physical information, the appropriate analysis methods of which can lead to the clear identification of the nature of the fault. A novel procedure is presented for construction of fault diagnosis dictionary through self-organization map (SOM). The experiments show that the bearing faults diagnosis dictionary could be effectively applied in the vibration pattern recognition for a roller bearing system.
  • Keywords
    fault diagnosis; mechanical engineering computing; rolling bearings; self-organising feature maps; vibrations; rolling bearing faults; self-organizing map-based fault dictionary; vibration pattern recognition; vibration signal; Ball bearings; Data mining; Dictionaries; Educational institutions; Fault diagnosis; Feature extraction; Neurons; Rolling bearings; Testing; Vibrations; Self-organization Map; Vibration signa; faults diagnosis dictionary; pattern recognition; physical information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.107
  • Filename
    4667152