• Author/Authors

    U. Kruger، نويسنده , , Y. Zhou and G.W. Irwin، نويسنده ,

  • DocumentNumber
    1384624
  • Title Of Article

    Improved principal component monitoring of large-scale processes

  • شماره ركورد
    11525
  • Latin Abstract
    In this work, the integration of ARMA filters into the multivariate statistical process control (MSPC) framework is presented to improve the monitoring of large-scale industrial processes. As demonstrated in the paper, such filters can remove auto-correlation from the monitored variables to avoid the production of false alarms. This is exemplified by application studies to a synthetic example from the literature and to the Tennessee Eastman benchmark process.
  • From Page
    879
  • NaturalLanguageKeyword
    ARMA filters , Auto-correlated process variables , multivariate statistical process control
  • JournalTitle
    Studia Iranica
  • To Page
    888
  • To Page
    888