• DocumentCode
    3309525
  • Title

    Condition monitoring architecture: To reduce total cost of ownership

  • Author

    Bechhoefer, Eric ; Morton, Brogan

  • Author_Institution
    NRG Syst., Hinesburg, VT, USA
  • fYear
    2012
  • fDate
    18-21 June 2012
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    The lack of widespread adoption of condition monitoring systems (CMS) in wind turbines is due, in part, to the high total cost of ownership. After the initial purchase, there is installation, Information Technology (servers/database/software support) and knowledge creation cost. Knowledge creation refers to the ability of the CMS to provide the operator with actionable information. Presented is a CMS architecture which reduces the total cost of ownership by reducing hardware cost (MEMS based sensor and local processing), reducing IT cost by deploying to a compute cloud, and reducing the cost of knowledge creation by incorporating advanced digital signal processing and decision support algorithms into the CMS application.
  • Keywords
    cloud computing; computerised monitoring; condition monitoring; decision support systems; power engineering computing; signal processing; wind turbines; CMS architecture; IT cost; compute cloud; condition monitoring architecture; condition monitoring systems; decision support algorithms; digital signal processing; information technology; knowledge creation cost; total ownership cost reduction; wind turbines; Accelerometers; Computer architecture; Gears; Micromechanical devices; Shafts; Vibrations; Wind turbines; MEMS sensor; cloud computing; condition monitoring; decision algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and Health Management (PHM), 2012 IEEE Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    978-1-4673-0356-9
  • Type

    conf

  • DOI
    10.1109/ICPHM.2012.6299509
  • Filename
    6299509