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Fault diagnosis for the Space Shuttle main engineA conceptual design of a model-based fault detection and diagnosis system is developed for the Space Shuttle main engine. The design approach consists of process modeling, residual generation, and fault detection and diagnosis. The engine is modeled using a discrete time, quasilinear state-space representation. Model parameters are determined by identification. Residuals generated from the model are used by a neural network to detect and diagnose engine component faults. Fault diagnosis is accomplished by training the neural network to recognize the pattern of the respective fault signatures. Preliminary results for a failed valve, generated using a full, nonlinear simulation of the engine, are presented. These results indicate that the developed approach can be used for fault detection and diagnosis. The results also show that the developed model is an accurate and reliable predictor of the highly nonlinear and very complex engine.
Document ID
19920045513
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Duyar, Ahmet
(Florida Atlantic University Boca Raton, United States)
Merrill, Walter
(NASA Lewis Research Center Cleveland, OH, United States)
Date Acquired
August 15, 2013
Publication Date
April 1, 1992
Publication Information
Publication: Journal of Guidance, Control, and Dynamics
Volume: 15
ISSN: 0731-5090
Subject Category
Spacecraft Propulsion And Power
Accession Number
92A28137
Distribution Limits
Public
Copyright
Other

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