A New Hybrid Fault Prognosis Method for MFS Systems Based on Distributed Neural Networks and Recursive Bayesian Algorithm

This article introduces a new hybrid prognosis method to predict a remaining useful lifetime (RUL) of multi-functional spoiler (MFS) systems. The MFS is vital to the healthy operation of aircraft spoiler control systems, and any fault or failure in these systems could compromise the safe operation o...

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Bibliographic Details
Published in:	IEEE systems journal Vol. 14; no. 4; pp. 5407 - 5416
Main Authors:	Kordestani, Mojtaba, Samadi, M. Foad, Saif, Mehrdad
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Aircraft Aircraft control Algorithms Atmospheric modeling Bayes methods Bayesian analysis Degradation model Failure Fault diagnosis fault prognosis Neural networks Parameter estimation Prognosis Prognostics and health management remaining useful life Uncertainty
ISSN:	1932-8184, 1937-9234
Online Access:	Get full text
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