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Distributed Data Mining for Aircraft Health Management Project

Summary

Type of release
a one-off release of a single dataset

Data Licence
Not Applicable

Content Licence
Creative Commons CCZero

Verification
automatically awarded

Release Date
9 April 2015
Modified Date
8 July 2015
Publishers
National Aeronautics and Space Administration
Keywords
ames-research-center, completed, project
Identifier
distributed-data-mining-for-aircraft-health-management-project-3f862
Landing Page
http://techport.nasa.gov/view/9689
Maintainers
TECHPORT SUPPORT hq-techport@mail.nasa.gov
Language
en-US

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Description

NASA, DoD, and commercial aircraft operators need to transform vast amounts of aircraft data accumulated in distributed databases into actionable knowledge. We propose distributed algorithms for data-driven health monitoring on aircraft, aircraft fleet, and national airspace levels. The proposed algorithms are based on distributed optimization formulation, and, unlike existing distributed processing methods, have rigorous guarantees of producing the same results as centralized processing would do. Our algorithms will be implemented in an open scalable framework that allows integrating distributed data and federated third party algorithms for anomaly detection, diagnosis, prediction, and prognosis. We will apply the proposed approach to aircraft performance monitoring from FOQA data. We will train regression models of aircraft performance using distributed agents associated with different data sets, locations, and organizations. The trained models will be then used for anomaly detection, diagnosis (fault isolation), prognosis (forecasting), and mitigation (decision support). This project will develop web-based distributed open architecture software implementing the proposed optimization-based approaches and demonstrate scalability to at least 10 TB of data. Besides the developed algorithms, we will explore integration of third party algorithms into the distributed environment. The developed technologies will be applicable to a broad range of aircraft-related and other problems.

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This dataset has been created by US Government which means it is required to be in the public domain. However US copyright law only allows open access by US citizens, we have assumed the data is equivalently licensed as CC0 for the rest of the world as this is in the spirit of the US Government’s Open Data policy.

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