JOURNAL ARTICLE

Algorithms for real-time fault detection of the Space Shuttle Main Engine

Abstract

This paper reports on the results of a program to develop and demonstrate concepts related to a realtime health management system (HMS) for the Space Shuttle Main Engine (SSME). An HMS framework was developed on the basis of a top-down analysis of the current rocket engine failure modes and the engine monitoring requirements. One result of Phase I of this program was the identification of algorithmic approaches for detecting failures of the SSME. Three different analytical techniques were developed which demonstrated the capability to detect failures significantly earlier than the existing redlines. Based on promising initial results, Phase II of the program was initiated to further validate and refine the fault detection strategy on a large data base of 140 SSME test firings, and implement the resultant algorithms in real time. The paper begins with an overview of the refined algorithms used to detect failures during SSME start-up and main-stage operation. Results of testing these algorithms on a data base of nominal and off-nominal SSME test firings is discussed. The paper concludes with a discussion of the performance of the algorithms operating on a real-time computer system.

Keywords:
Space Shuttle Computer science Fault detection and isolation Space (punctuation) Real-time computing Aerospace engineering Artificial intelligence Operating system Engineering

Metrics

5
Cited By
1.28
FWCI (Field Weighted Citation Impact)
1
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Statistical and Computational Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence

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