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    • A Novel RSPF Approach to Prediction of High-Risk, Low-Probability Failure Events

    Metadata Updated: February 6, 2026

    Particle filters (PF) have been established as the de facto state of the art in failure prognosis, and particularly in the representation and management of uncertainty in long-term predictions when used in combination with outer feedback correction loops. This paper presents a novel Risk- Sensitive PF (RSPF) framework that complements the benefits of the classic approach, by representing the probability of rare and costly events within the formulation of the nonlinear dynamic equation that describes the evolution of the fault condition in time. The performance of this approach is thoroughly compared using a set of proposed metrics for prognosis results. The scheme is illustrated with real vibration feature data from a fatigue-driven fault in a critical aircraft component.

    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.

    Downloads & Resources

    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date February 6, 2026
    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 February 6, 2026
    Publisher Dashlink
    Maintainer
    Identifier DASHLINK_729
    Data First Published 2013-05-09
    Data Last Modified 2025-03-31
    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 7a47898a-6797-4145-8a32-2a26ff8929d9
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://c3.nasa.gov/dashlink/resources/729/
    Program Code 026:029
    Source Datajson Identifier True
    Source Hash 69c62b723c4fe9f56b595eb3d6d54b02eb6063aa75c2ce3c7596cc5ec77e3cfe
    Source Schema Version 1.1

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