• DocumentCode
    2339715
  • Title

    Real-Time Data Mining in Magnetic Flux Leakage Detecting in Boiler Pipeline

  • Author

    Ke MinYi ; Liao Pan ; Song XiaoChun

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Hubei Univ. of Technol., Wuhan, China
  • Volume
    2
  • fYear
    2010
  • fDate
    18-20 Dec. 2010
  • Firstpage
    130
  • Lastpage
    133
  • Abstract
    For boiler in magnetic flux leakage testing data characteristics on the basis of full analysis, Combining the application of industrial control integrated automation needs, proposed the pipeline magnetic flux leakage testing data mining system framework. Through analysis of magnetic flux leakage pipeline inspection data and mines the key data. It could be better to achieve detection and prediction of the pipe flaw.
  • Keywords
    boilers; condition monitoring; data mining; magnetic flux; mechanical engineering computing; mechanical testing; pipelines; boiler pipeline; magnetic flux leakage detection; magnetic flux leakage test; pipe flaw detection; pipe flaw prediction; pipeline inspection; realtime data mining; Data mining; Magnetic flux leakage; Real-time; Time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Manufacturing and Automation (ICDMA), 2010 International Conference on
  • Conference_Location
    ChangSha
  • Print_ISBN
    978-0-7695-4286-7
  • Type

    conf

  • DOI
    10.1109/ICDMA.2010.243
  • Filename
    5701366