• DocumentCode
    2520125
  • Title

    Soft sensors and artificial intelligence for nuclear fusion experiments

  • Author

    Rizzo, Alessandro

  • Author_Institution
    Dipt. di Elettrotec. ed Elettron., Politec. di Bari, Bari, Italy
  • fYear
    2010
  • fDate
    26-28 April 2010
  • Firstpage
    1068
  • Lastpage
    1072
  • Abstract
    Soft sensors are mathematical models able to estimate process variables. They can work in parallel with hardware sensors, and can be implemented at a low-cost on existing hardware. They are useful for back-up of measuring devices, reduction of measuring hardware requirements, real-time estimation for monitoring and control, sensor validation, fault detection and diagnosis, what-if analysis. In industrial applications, data-driven approaches, especially based on soft-computing techniques, are very promising. In this paper we review important issues in soft sensor design and applications, especially concerning the applications in the field of nuclear fusion.
  • Keywords
    artificial intelligence; fault diagnosis; mathematical analysis; nuclear fusion; power engineering computing; artificial intelligence; data-driven approaches; fault detection; fault diagnosis; hardware sensors; mathematical models; nuclear fusion experiments; parallel sensors; real-time estimation; sensor validation; soft sensors; soft-computing techniques; Artificial intelligence; Fault detection; Fusion reactors; Hardware; Intelligent sensors; Mathematical model; Monitoring; Physics; Pollution measurement; Sensor fusion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    MELECON 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference
  • Conference_Location
    Valletta
  • Print_ISBN
    978-1-4244-5793-9
  • Type

    conf

  • DOI
    10.1109/MELCON.2010.5476042
  • Filename
    5476042