An expert system for fault diagnosis in a Space Shuttle main engineThe detection and diagnosis of SSME faults in an early stage is important in order to allow enough time for fault preventive or corrective measurements. Since most of the faults in a complex system like SSME develop rapidly, early detection and diagnosis of faults is critical for the survival of space vehicles. An expert system has been designed for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations. This paper describes an innovative machine learning approach which is employed for the automatic training of this expert system.
Document ID
19900053493
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Ali, Moonis (Tennessee Univ. Tullahoma, TN, United States)
Gupta, U. K. (Tennessee, University Tullahoma, United States)