A Bayesian Framework for Remaining Useful Life Estimation

Metadata Updated: February 28, 2019

The estimation of remaining useful life (RUL) of a faulty component is at the center of system prognostics and health management. It gives operators a potent tool in decision making by quantifying how much time is left until functionality is lost. This is especially true for aerospace systems, where unanticipated subsystem downtime may lead to catastrophic failures. RUL prediction needs to contend with multiple sources of error like modeling inconsistencies, system noise and degraded sensor fidelity. Bayesian theory of uncertainty management provides a way to contain these problems by integrating out the nuisance variables. We use the Relevance Vector Machine (RVM), for model development. RVM is a Bayesian treatment of the well known Support Vector Machine (SVM), a kernel-based regression/classification technique. This model is next used in a Particle Filter (PF) framework. Statistical estimates of the noise in the system and anticipated operational conditions are processed to provide estimates of RUL in the form of a probability density function (PDF). Validation of this approach on experimental data collected from Li-ion batteries is presented.

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

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Metadata Created Date August 1, 2018
Metadata Updated Date February 28, 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 February 28, 2019
Publisher Dashlink
Unique Identifier DASHLINK_747
Miryam Strautkalns
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
Harvest Object Id 543657a8-f1d9-49ad-80be-6eabc3a06094
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2013-05-13
Homepage URL https://c3.nasa.gov/dashlink/resources/747/
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 bac9142a49d125639b6280f2a94badca776b3a4a
Source Schema Version 1.1

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