• DocumentCode
    3216780
  • Title

    A novel analytical framework for qualitative Model-Based Fault Diagnosis

  • Author

    Baniardalani, Sobhi ; Askari, Javad ; Afzalian, Ali A.

  • Author_Institution
    Electr. & Comput. Eng. Dept., Isfahan Univ. of Technol., Isfahan, Iran
  • fYear
    2010
  • fDate
    9-11 June 2010
  • Firstpage
    1929
  • Lastpage
    1934
  • Abstract
    This paper presents a unified analytical framework for qualitative Model-Based Fault Diagnosis (MBFD), similar to the quantitative MBFD. Dioid Algebra is used in addition to ordinary Algebra for simulation qualitative models. The framework is illustrated and adapted in details for three main qualitative diagnostic methods which employ Stochastic, Non-Deterministic, and Timed Automata, respectively. Using the proposed methodology, we are able to compute quantitative residuals for qualitative models. Therefore some useful and practical computational tasks can be carried out on the obtained residuals. One of the main contributions of the paper is introducing a new approach to qualitative structured residual generation, which is applied to timed automata models.
  • Keywords
    Algebra; Automata; Automatic control; Automation; Fault diagnosis; Filters; Java; Pattern recognition; Robustness; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation (ICCA), 2010 8th IEEE International Conference on
  • Conference_Location
    Xiamen, China
  • ISSN
    1948-3449
  • Print_ISBN
    978-1-4244-5195-1
  • Electronic_ISBN
    1948-3449
  • Type

    conf

  • DOI
    10.1109/ICCA.2010.5524167
  • Filename
    5524167