• DocumentCode
    438884
  • Title

    Proactive health management for automated equipment: from diagnostics to prognostics

  • Author

    Zhang, D.H. ; Zhang, J.B. ; Luo, M. ; Zhao, Y.Z. ; Wong, M.M.

  • Author_Institution
    Singapore Inst. of Manufacturing Technol., Nanyang, Singapore
  • Volume
    1
  • fYear
    2004
  • fDate
    6-9 Dec. 2004
  • Firstpage
    479
  • Abstract
    In this paper, generic methodologies for prognostic machinery health management are discussed and a framework is proposed for extending prognostic capabilities to conventional maintenance and diagnostic system (MDS). Two specific techniques that can be used to extract knowledge and rules for fault prediction are discussed. These techniques are based on the analysis of historical data gathered by the MDS. The paper further elaborates on knowledge based real-time failure prediction and recommends a diagnostics-to-prognostics approach that enables traditional reactive MDS to be transformed into proactive health management (PHM) systems.
  • Keywords
    condition monitoring; fault diagnosis; knowledge acquisition; machinery; mechanical engineering computing; preventive maintenance; real-time systems; automated equipment; diagnostics-to-prognostics approach; fault prediction; knowledge based real-time failure prediction; knowledge extraction; maintenance and diagnostic system; proactive health management systems; prognostic machinery health management; Computerized monitoring; Condition monitoring; Data mining; Fault detection; Intelligent sensors; Knowledge management; Machinery; Maintenance; Military computing; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
  • Print_ISBN
    0-7803-8653-1
  • Type

    conf

  • DOI
    10.1109/ICARCV.2004.1468872
  • Filename
    1468872