Engineering topics

Whitehead, B. A.

Publications and source records attributed to Whitehead, B. A..

3 records

NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗

NASA NTRS1993

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

The 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.

Lo, C. F.↗

NASA NTRS1992

Automatic detection of anomalies in Space Shuttle Main Engine turbopumps

A prototype expert system (developed on both PC and Symbolics 3670 lisp machine) for detecting anomalies in turbopump vibration data has been tested with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine (SSME). The expert system has been utilized to analyze vibration data from each of the following SSME components: high-pressure oxidizer turbopump, high-pressure fuel turbopump, low-pressure fuel turbopump, and preburner boost pump. The expert system locates and classifies peaks in the power spectral density of each 0.4-sec window of steady-state data. Peaks representing the fundamental and harmonic frequencies of both shaft rotation and bearing cage rotation are identified by the expert system. Anomalies are then detected on the basis of sequential criteria and two threshold criteria set individually for the amplitude of each of these peaks: a prior threshold used during the first few windows of data in a test, and a posterior threshold used thereafter. In most cases the anomalies detected by the expert system agree with those reported by NASA. The two cases where there is significant disagreement will be further studied and the system design refined accordingly.

Lo, Ching F.↗