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
Link To Document :
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