• DocumentCode
    749379
  • Title

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

  • Author

    Kirkland, Lany V. ; Dean, Jeffrey S. ; Harm, Mike

  • Author_Institution
    US Air Force, UT, USA
  • Volume
    10
  • Issue
    1
  • fYear
    1995
  • fDate
    1/1/1995 12:00:00 AM
  • Firstpage
    28
  • Lastpage
    30
  • 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; circuit testing; electric current measurement; fault diagnosis; fault location; neural net architecture; ATE; ATS power supply; circuit faults diagnosis; current flow; neural network; power supply current monitoring; sensors; Application software; Circuit faults; Circuit testing; Computer architecture; Current supplies; Monitoring; Neural networks; Packaging; Performance evaluation; Power supplies;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    0885-8985
  • Type

    jour

  • DOI
    10.1109/62.370461
  • Filename
    370461