• DocumentCode
    3474557
  • Title

    Comparison of gross errors detection methods in process data

  • Author

    Maquin, Didier ; Ragot, José

  • Author_Institution
    Centre de Recherche en Autom. de Nancy, CNRS, Vandoeuvre, France
  • fYear
    1991
  • fDate
    11-13 Dec 1991
  • Firstpage
    2254
  • Abstract
    The authors first discuss the fundamental problem of data reconciliation. They then prove the equivalence of some tests commonly used for gross error detection: parity vector, normalized corrective terms, the generalized likelihood ratio test, and variation of the residual criterion after measurement deletion
  • Keywords
    data analysis; error analysis; identification; measurement errors; signal detection; data reconciliation; generalized likelihood ratio test; gross errors detection; measurement errors; normalized corrective terms; parity vector; process data; residual criterion; Automatic testing; Data engineering; Equations; Error correction; Hardware; Instruments; Iterative methods; OFDM modulation; Power engineering and energy; Power measurement; Redundancy; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
  • Conference_Location
    Brighton
  • Print_ISBN
    0-7803-0450-0
  • Type

    conf

  • DOI
    10.1109/CDC.1991.261549
  • Filename
    261549