Nikunj C. Oza's Publications

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Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Mark Schwabacher, Nikunj C. Oza, and Bryan Matthews. In AIAA Infotech@Aerospace Conference, 2007.

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Abstract

This paper describes the initial results of applying four machine-learning-based unsupervised anomaly detection algorithms—Orca, GritBot, the Inductive Monitoring System, and one-class Support Vector Machines—to historical data from the Space Shuttle Main Engine. The paper describes five anomalies detected by the four algorithms.

BibTeX Entry

@inproceedings{scoz07,
	author = {Mark Schwabacher, Nikunj C. Oza, and Bryan Matthews},
	title = {Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring},
	booktitle={AIAA Infotech@Aerospace Conference},
	abstract={This paper describes the initial results of applying four machine-learning-based unsupervised anomaly detection algorithmsÑOrca, GritBot, the Inductive Monitoring System, and one-class Support Vector MachinesÑto historical data from the Space Shuttle Main Engine. The paper describes five anomalies detected by the four algorithms.},
	bib2html_pubtype = {Other Conference},
	bib2html_rescat = {Fault Detection},
	year = {2007}
}

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