Hierarchical Active Fault Diagnosis for Stochastic Large Scale Systems with Coupled Faults

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959774" target="_blank" >RIV/49777513:23520/20:43959774 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.23919/FUSION45008.2020.9190304" target="_blank" >https://doi.org/10.23919/FUSION45008.2020.9190304</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/FUSION45008.2020.9190304" target="_blank" >10.23919/FUSION45008.2020.9190304</a>

Result language
angličtina
Original language name
Hierarchical Active Fault Diagnosis for Stochastic Large Scale Systems with Coupled Faults
Original language description
The paper deals with the active fault diagnosis of large scale stochastic systems with faults modeled as mutually dependent Markov chains. The system is described by multiple models representing fault-free and faulty behavior of the system. The aim of the active fault detector in addition to detecting the faults is to excite the system to improve the detection quality. The algorithm consists of two stages: the off-line design of the Bellman function providing the optimal excitation and the on-line estimation, which generates the decisions and selects the optimal excitation according to the Bellman function. In particular, the paper focuses on the online estimation and proposes an algorithm in the hierarchical architecture. The local nodes estimate the continuous state of the subsystems, select the optimal excitations and send local likelihoods to the central node. The central node generates the decisions and submits the respective model probabilities to the local nodes. The performance of the proposed algorithm is validated using a simple numerical example.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION)
ISBN
978-0-578-64709-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
Rustenburg
Event location
Rustenburg, Jihoafrická republika
Event date
Jul 6, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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