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Proceedings Paper

Investigation of neural networks for F-16 fault diagnosis: II. System performance
Author(s): Richard J. McDuff; Patrick K. Simpson
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Paper Abstract

We have examined the use of neural networks as a potential method of solving the multiple fault diagnostics problem that is when one symptom leads to several faults many symptoms leadto one fault or many symptoms lead to many faults. Current methods addressing this problem are brittle and slow. We have approached diagnostics from a pattern classification perspective in that we have constructed an input pattern from symptoms and classified that symptom pattern to an appropriate output class that corresponds to the fault that occurred. The system description was described in the first part of this two-part paper . In this second part we will report on the performance of the system. 1.

Paper Details

Date Published: 1 August 1990
PDF: 14 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21155
Show Author Affiliations
Richard J. McDuff, General Dynamics Corp. (United States)
Patrick K. Simpson, General Dynamics Corp. (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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