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
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;
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
DOI :
10.1109/AUTEST.1994.381556