Unsupervised Anomaly Detection for Liquid-Fueled Rocket Prop...

Metadata Updated: May 2, 2019

Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring.

Abstract: This article describes the results of applying four unsupervised anomaly detection algorithms to data from two rocket propulsion testbeds. The first testbed uses historical data from the Space Shuttle Main Engine. The second testbed uses data from an experimental rocket engine test stand located at NASA Stennis Space Center. The article describes nine anomalies detected by the four algorithms. The four algorithms use four different definitions of anomalousness. Orca uses a nearest-neighbor approach, defining a point to be an anomaly if its nearest neighbors in the data space are far away from it. The Inductive Monitoring System clusters the training data, and then uses the distance to the nearest cluster as its measure of anomalousness. GritBot learns rules from the training data, and then classifies points as anomalous if they violate these rules. One-class support vector machines map the data into a high-dimensional space in which most of the normal points are on one side of a hyperplane, and then classify points on the other side of the hyperplane as anomalous. Because of these different definitions of anomalousness, different algorithms detect different anomalies. We therefore conclude that it is useful to use multiple algorithms.

Access & Use Information

Public: This dataset is intended for public access and use. License: U.S. Government Work

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Dates

Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date May 2, 2019
Publisher Dashlink
Unique Identifier DASHLINK_171
Maintainer
MARK SCHWABACHER
Maintainer Email
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Datagov Dedupe Retained 20190501230127
Harvest Object Id f1569103-ba94-479f-b494-9c0bbd6a4860
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2010-09-22
Homepage URL https://c3.nasa.gov/dashlink/resources/171/
License http://www.usa.gov/publicdomain/label/1.0/
Data Last Modified 2018-07-19
Program Code 026:029
Source Datajson Identifier True
Source Hash 90858719b79d986044169cd9636a9a76f4b5f052
Source Schema Version 1.1

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