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Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networksThe statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.
Document ID
19930065675
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Lo, C. F.
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Wu, K.
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Whitehead, B. A.
(Tennessee Univ. Tullahoma, United States)
Date Acquired
August 16, 2013
Publication Date
June 1, 1993
Subject Category
Spacecraft Propulsion And Power
Report/Patent Number
AIAA PAPER 93-1777
Meeting Information
Meeting: AIAA, SAE, ASME, and ASEE, Joint Propulsion Conference and Exhibit
Location: Monterey, CA
Country: United States
Start Date: June 28, 1993
End Date: June 30, 1993
Sponsors: ASEE, ASME, AIAA, SAE
Accession Number
93A49672
Funding Number(s)
CONTRACT_GRANT: NAG8-166
Distribution Limits
Public
Copyright
Other

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