• DocumentCode
    2679134
  • Title

    Soft Fault Diagnosis of Analog Circuit Using Transfer Function Coefficients

  • Author

    Kavithamani, A. ; Manikandan, V. ; Devarajan, N.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Coimbatore Inst. of Technol., Coimbatore, India
  • fYear
    2011
  • fDate
    20-22 July 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A method to identify parametric faults occurring in analog circuits is proposed in this paper. This method uses transfer function coefficients to identify faults in analog circuits as these coefficients are sensitive to the parameters of the circuit. Using Monte Carlo simulation each parameter of the circuit is varied within its tolerance limit and the minimum and maximum values of each coefficient are found for faulty and fault free conditions. While testing the coefficients are found for the injected fault and if all coefficients are within the predetermined bound limits of any fault conditions then the circuit is confirmed to have that particular fault. In the same manner all single faults occurring in the analog circuits are identified. The proposed method is illustrated through second order sallenkey band pass filter circuit. Results have confirmed that the proposed method can diagnose single parametric faults in analog circuits efficiently.
  • Keywords
    Monte Carlo methods; band-pass filters; circuit reliability; fault diagnosis; transfer functions; Monte Carlo simulation; analog circuit; parametric fault; second order sallenkey band pass filter circuit; soft fault diagnosis; transfer function coefficients; Analog circuits; Band pass filters; Circuit faults; Dictionaries; Fault diagnosis; Monte Carlo methods; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Process Automation, Control and Computing (PACC), 2011 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-61284-765-8
  • Type

    conf

  • DOI
    10.1109/PACC.2011.5978952
  • Filename
    5978952