• DocumentCode
    2101468
  • Title

    Fault diagnosis using dynamic finite-state automaton models

  • Author

    Xi, Yun-Xia ; Lim, Khiang-Wee ; Ho, Weng-Khuen ; Preisig, Heinz A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    484
  • Abstract
    The paper continues the development of an algorithm for fault diagnosis using a Finite-state Automaton (FSA) model. The plant is represented by a set of Finite-state Automaton Tables (FATS) that can be dynamically generated for normal input and for fault input conditions. A fault detection and isolation algorithm compares actual plant events with that predicted by the FATS. The paper defines fault diagnosability of the FATS, identifies some conditions for nondiagnosability, discusses guidelines for choosing the set of boundaries that helps define the FATS and provides a method for dynamically computing the FATS. We illustrate the application of the approach on a batch system
  • Keywords
    computerised instrumentation; fault diagnosis; finite state machines; modelling; FATS; FSA model; dynamic computing; dynamic finite-state automaton models; fault detection and isolation algorithm; fault diagnosability; fault diagnosis; fault input conditions; nondiagnosability; normal input; plant events; Automata; Discrete event systems; Fats; Fault detection; Fault diagnosis; Guidelines; Industrial plants; Physics; Process control; Robust control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
  • Conference_Location
    Denver, CO
  • Print_ISBN
    0-7803-7108-9
  • Type

    conf

  • DOI
    10.1109/IECON.2001.976530
  • Filename
    976530