NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Artificial intelligence techniques for ground test monitoring of rocket enginesAn expert system is being developed which can detect anomalies in Space Shuttle Main Engine (SSME) sensor data significantly earlier than the redline algorithm currently in use. The training of such an expert system focuses on two approaches which are based on low frequency and high frequency analyses of sensor data. Both approaches are being tested on data from SSME tests and their results compared with the findings of NASA and Rocketdyne experts. Prototype implementations have detected the presence of anomalies earlier than the redline algorithms that are in use currently. It therefore appears that these approaches have the potential of detecting anomalies early eneough to shut down the engine or take other corrective action before severe damage to the engine occurs.
Document ID
19900055094
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Ali, Moonis
(Tennessee Univ. Space Inst. Tullahoma, TN, United States)
Gupta, U. K.
(Tennessee, University Tullahoma, United States)
Date Acquired
August 14, 2013
Publication Date
July 1, 1990
Subject Category
Ground Support Systems And Facilities (Space)
Report/Patent Number
AIAA PAPER 90-2384
Accession Number
90A42149
Funding Number(s)
CONTRACT_GRANT: NAG8-121
Distribution Limits
Public
Copyright
Other

Available Downloads

There are no available downloads for this record.
No Preview Available