• DocumentCode
    2083068
  • Title

    A MT-NT-MILP combined method for gross error detection and data reconciliation

  • Author

    Sun, Shaochao ; Dao, Huang ; Gong, Yanxue

  • Author_Institution
    School of Information Science and Engineering; East China University of Science and Technology Shanghai 20037, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    3439
  • Lastpage
    3442
  • Abstract
    Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. In this paper, a MT-NT-MILP (MNM)combined method is developed for gross error detection and data reconciliation for industrial application. An improved MT-NT method is proposed in order to generate gross error candidates before data rectification. Candidates are used in the MILP objective function to improve the efficiency by reducing the number of binary variables. Simulation results show that the method is effective especially in a large-scale problem.
  • Keywords
    Chemical engineering; Equations; Graphics; Materials; Mathematical model; Measurement uncertainty; Robustness; MILP; MT; NT; data rectification; graphic theory; gross error detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5688570
  • Filename
    5688570