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    • Comparative Analysis of Data-Driven Anomaly Detection Methods

    Metadata Updated: April 11, 2025

    This paper provides a review of three different advanced machine learning algorithms for anomaly detection in continuous data streams from a ground-test firing of a subscale Solid Rocket Motor (SRM). This study compares Orca, one-class support vector machines, and the Inductive Monitoring System (IMS) for anomaly detection on the data streams. We measure the performance of the algorithm with respect to the detection horizon for situations where fault information is available. These algorithms have been also studied by the present authors (and other co-authors) as applied to liquid propulsion systems. The trade space will be explored between these algorithms for both types of propulsion systems.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date April 11, 2025
    Data Update Frequency irregular

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date April 11, 2025
    Publisher Dashlink
    Maintainer
    Identifier DASHLINK_151
    Data First Published 2010-09-22
    Data Last Modified 2025-04-01
    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
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 9f04d8d6-be2d-4fa4-8512-4b474794c445
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://c3.nasa.gov/dashlink/resources/151/
    Program Code 026:029
    Source Datajson Identifier True
    Source Hash 7d0fac363f772d5bded56fb8bad547397773db84ebd11a4b4aa9019f73c80578
    Source Schema Version 1.1

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