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Experimental Validation of a Prognostic Health Management System for Electro-Mechanical Actuators

Metadata Updated: December 7, 2023

The work described herein is aimed to advance prognostic health management solutions for electro-mechanical actuators and, thus, increase their reliability and attractiveness to designers of the next generation aircraft and spacecraft. In pursuit of this goal the team adopted a systematic approach by starting with EMA FMECA reviews, consultations with EMA manufacturers, and extensive literature reviews of previous efforts. Based on the acquired knowledge, nominal/off-nominal physics models and prognostic health management algorithms were developed. In order to aid with development of the algorithms and validate them on realistic data, a testbed capable of supporting experiments in both laboratory and flight environment was developed. Test actuators with architectures similar to potential flight-certified units were obtained for the purposes of testing and realistic fault injection methods were designed. Several hundred fault scenarios were created, using permutations of position and load profiles, as well as fault severity levels. The diagnostic system was tested extensively on these scenarios, with the test results demonstrating high accuracy and low numbers of false positive and false negative diagnoses. The prognostic system was utilized to track fault progression in some of the fault scenarios, predicting the remaining useful life of the actuator. A series of run-to-failure experiments were conducted to validate its performance, with the resulting error in predicting time to failure generally lesser than 10% error. While a more robust validation procedure would require dozens more experiments executed under the same conditions (and, consequently, more test articles destroyed), the current results already demonstrate the potential for predicting fault progression in this type of devices. More prognostic experiments are planned for the next phase of this work, including investigation and comparison of other prognostic algorithms (such as various types of Particle Filter and GPR), addition of new fault types, and execution of prognostic experiments in flight environment.

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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Metadata Created Date November 12, 2020
Metadata Updated Date December 7, 2023
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date December 7, 2023
Publisher Dashlink
Identifier DASHLINK_711
Data First Published 2013-04-26
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id 32dd6741-9128-40c3-8323-d693b5d595b2
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL
Program Code 026:029
Source Datajson Identifier True
Source Hash 55bbacdf1b4fff6eb0a2cf9cb94c7ed6da5c32a79b691583fd6259d8588a2145
Source Schema Version 1.1

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