• DocumentCode
    2542607
  • Title

    The application of data mining for marine diesel engine fault detection

  • Author

    Chen Yongzhi ; Yu Yonghua ; Peng Zhangming

  • Author_Institution
    Sch. of Energy & Power Eng. of Wuhan, Univ. of Technol., Wuhan, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1430
  • Lastpage
    1433
  • Abstract
    Early fault detection for marine diesel engines is very important to ensure reliable operation throughout the course of their service. An early fault detection method is introduced in this paper based on the thermal parameters, and a fault predication system for marine diesel engine is developed based on abnormal data mining technology, which acquires the thermal parameters of the diesel engine from the local safety, alarm and control system through field bus, manages the data by database, and predicts the operation condition through statistic and data miming technology. It is found that the abnormal data mining is effective to fault detection at the early stage.
  • Keywords
    data mining; diesel engines; fault diagnosis; marine systems; reliability; safety; abnormal data mining technology; alarm system; control system; data management; fault predication system; field bus; local safety; marine diesel engine fault detection method; reliable operation; statistic technology; thermal parameters; Data mining; Data models; Databases; Diesel engines; Fault detection; Temperature distribution; Testing; Data Mining; Database; Fault Detection; Marine Diesel Engine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6233807
  • Filename
    6233807