• DocumentCode
    183918
  • Title

    FAST: A fault analysis software tool

  • Author

    Duatis, Jordi ; Angulo, Cecilio ; Puig, Vicenc

  • Author_Institution
    Cerdanyola del Valles, NTE-SENER, Cerdanyola, Spain
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    376
  • Lastpage
    381
  • Abstract
    This paper introduces the Fault Analysis Software Tool (FAST) which from a simplified description of any process is able to perform the structural analysis and systematically obtain the analytical redundancies to perform fault diagnosis, identifying the fault and the associated faulty component. The proposed tool can operate in different ways: stand alone in simulation mode, off-line; reading the measured values from data files, or on-line connected to the process through an OPC interface, enabling for connecting to a SCADA system for supervisory control. When running in on-line mode, in case of a fault, FAST is able to indicate the faulty device by means of updating the process database such that the SCADA can display and record the fault. Early countermeasures can be implemented, either by automatic reconfiguration of the system or by operator intervention. The fault diagnosis algorithms implemented in the tool are described and illustrated using the well-known two-tank system case study.
  • Keywords
    SCADA systems; fault diagnosis; redundancy; software tools; FAST; OPC interface; SCADA system; analytical redundancy; data files; fault analysis software tool; fault diagnosis; fault display; fault recording; faulty component identification; off-line mode; online mode; process database update; simulation mode; structural analysis; supervisory control; Algorithm design and analysis; Fault diagnosis; Joining processes; Redundancy; Software algorithms; Valves; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications (CCA), 2014 IEEE Conference on
  • Conference_Location
    Juan Les Antibes
  • Type

    conf

  • DOI
    10.1109/CCA.2014.6981375
  • Filename
    6981375