• DocumentCode
    2514716
  • Title

    Monitoring power supply current and using a neural network routine to diagnose circuit faults

  • Author

    Kirkland, Larry V. ; Dean, Jeffrey S.

  • Author_Institution
    TISA US Air Force, Hill AFB, UT, USA
  • fYear
    1994
  • fDate
    20-22 Sep 1994
  • Firstpage
    649
  • Lastpage
    651
  • Abstract
    As a circuit is tested, the current drawn from a power supply can vary as different functions are invoked by the test. The current draw can be plotted against time, showing a characteristic trace for the test performed. Sensors in the ATS power supply can be used to monitor the current flow during test execution. Defective components can be classified using a neural network according to the pattern of variation from the “trace” of a good card. This can be performed as a background function, with the network gaining in accuracy over time. This paper discusses the neural network routine for diagnosing circuit faults using monitored power supply current
  • Keywords
    automatic test equipment; computerised monitoring; data acquisition; electric current measurement; fault diagnosis; fault location; learning (artificial intelligence); neural net architecture; power supply circuits; ATS power supply; circuit faults diagnosis; current flow; defective components; electric current measurement; monitored power supply current; neural network routine; power supply current; Circuit faults; Circuit testing; Computer architecture; Current supplies; Monitoring; Neural networks; Packaging; Performance evaluation; Power supplies; Sensor phenomena and characterization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AUTOTESTCON '94. IEEE Systems Readiness Technology Conference. 'Cost Effective Support Into the Next Century', Conference Proceedings.
  • Conference_Location
    Anaheim, CA
  • Print_ISBN
    0-7803-1910-9
  • Type

    conf

  • DOI
    10.1109/AUTEST.1994.381556
  • Filename
    381556