Health management for aircraft system using Bayesian probability model

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Abstract

The health management for aircraft system is difficult problem when the system is rife with nonlinear/non-Gaussian time evolution, the model parameters and sensors measurements are subject to uncertainty, and the diagnosis task suffers from some real-Time constrains. This paper discusses the most relatively recent researches about Bayesian probability model, which focuses on the Bayesian networks (BNs), dynamic Bayesian network (DBN) and arithmetic circuit (AC), and then proposes an novel approach to build a robust dynamic arithmetic circuit (DAC) to successfully address this problem. The experiments results show that the DAC, compared with BN, AC and DBN, not only provides reliable online diagnosis under the presence of uncertainty, but also meets the strict time deadlines of health management.

Original languageEnglish
Title of host publicationAUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1203-1208
Number of pages6
ISBN (Electronic)9781509010875
DOIs
StatePublished - 17 Nov 2016
Event2016 IEEE/CSAA International Conference on Aircraft Utility Systems, AUS 2016 - Beijing, China
Duration: 10 Oct 201612 Oct 2016

Publication series

NameAUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems

Conference

Conference2016 IEEE/CSAA International Conference on Aircraft Utility Systems, AUS 2016
Country/TerritoryChina
CityBeijing
Period10/10/1612/10/16

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