Application of neural networks to the F/A-18 Engine Condition Monitoring System
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Authors
Gengo, Joseph Thomas
Subjects
neural networks
back propagation
Kohonen
F-18 IECMS report
back propagation
Kohonen
F-18 IECMS report
Advisors
Collins, D.J.
Date of Issue
1989-09
Date
September 1989
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Neural networks were applied to the Engine Condition and
Monitoring System of the F/A-18 aircraft. Due to recent fleet
experience with compressor blade failures in flight, neural
networks were applied to three engine conditions; flameout due
to compressor failures, normal operating conditions, and low
oil pressure conditions. An attempt was made to predict
compressor failure using the neural networks.
A back propagation and back propagation/Kohonen network
were successfully tested in recognizing the various conditions
with data previously unseen by the networks. Both networks
demonstrated promise in predicting failures although not
enough data was available for conclusive results.
Type
Thesis
Description
Series/Report No
Department
Aeronautics and Astronautics
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funding
Format
117 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.