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Informatics and Automation, 2022, Issue 21, volume 1, Pages 126–160
DOI: https://doi.org/10.15622/ia.2022.21.5
(Mi trspy1186)
 

This article is cited in 2 scientific papers (total in 2 papers)

Artificial Intelligence, Knowledge and Data Engineering

Hybrid network structures and their use in diagnosing complex technical systems

V. Yakimov, G. Maltsev

A.F. Mozhaysky military space academy
Abstract: An approach to the technical diagnostics of complex technical systems based on the results of telemetry information processing by an external monitoring and diagnostics system using hybrid network structures is proposed. The principle of constructing diagnostic complexes of complex technical systems is considered, which ensures the automation of the technical diagnostics process and is based on the use of models in the form of hybrid network structures for processing telemetric information, including multilayer neural networks and discrete Bayesian networks with stochastic learning. A model of changes in the parameters of complex technical systems technical state based on multilayer neural networks has been developed, which makes it possible to form a probabilistic assessment of attributing the current situation of complex technical system functioning to the set of functions considered situations according to individual telemetry parameters, and multilevel hierarchical model of complex technical systems technical diagnostics based on a discrete Bayesian network with stochastic learning, which allows aggregating the information received from neural network models and recognizing the current situation of complex technical system functioning. In the conditions of functioning emergencies of the complex technical system, according to the results of processing telemetric information, faulty functional units are localized and an explanation of the cause of the emergency is formed. The stages of complex technical systems technical diagnostics implementation using the proposed hybrid network structures in the processing of telemetric information are detailed. An example of using the developed approach to solving problems of spacecraft onboard system technical diagnostics is presented. The advantages of the proposed approach to the technical diagnostics of complex technical systems in comparison with the traditional approach based on analysis of telemetry parameters values belonging to the given tolerances are shown.
Keywords: complex technical system, technical diagnostics, reliability of functioning, Bayesian network, stochastic learning.
Received: 06.08.2021
Document Type: Article
UDC: 681.518.5
Language: Russian
Citation: V. Yakimov, G. Maltsev, “Hybrid network structures and their use in diagnosing complex technical systems”, Informatics and Automation, 21:1 (2022), 126–160
Citation in format AMSBIB
\Bibitem{YakMal22}
\by V.~Yakimov, G.~Maltsev
\paper Hybrid network structures and their use in diagnosing complex technical systems
\jour Informatics and Automation
\yr 2022
\vol 21
\issue 1
\pages 126--160
\mathnet{http://mi.mathnet.ru/trspy1186}
\crossref{https://doi.org/10.15622/ia.2022.21.5}
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  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Informatics and Automation
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