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Complex technical system condition diagnostics and prediction computerization
dc.contributor.author | Rudnichenko, N. | en |
dc.contributor.author | Vychuzhanin, V. | en |
dc.contributor.author | Polyvianchuk, A. | en |
dc.contributor.author | Mateichyk, V. | en |
dc.contributor.author | Полив'янчук, А. П. | uk |
dc.date.accessioned | 2022-05-16T09:24:22Z | |
dc.date.available | 2022-05-16T09:24:22Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Complex technical system condition diagnostics and prediction computerization. / N. Rudnichenko, V. Vychuzhanin, A. Polyvianchuk, V. Mateichyk // CEUR Workshop Proceedings. – 2020. – Vol. 2608. – P. 42-56. | en |
dc.identifier.issn | 1613-0073 | |
dc.identifier.uri | http://ir.lib.vntu.edu.ua//handle/123456789/35247 | |
dc.description.abstract | Based on the analysis of literary sources, the article sets the goal of forming a methodological application of information technology in diagnostics, as well as in predicting the state of complex technical systems. It is advisable to carry out a diagnostic assessment of the system failures risk based on modeling their components interaction. To achieve this goal, an informational cognitive model has been developed that allows for diagnosis to assess complex technical systems components failure risk. In order to provide a search for the failures causes of a complex technical system diagnosed subsystems components, a decision support model has been developed and researched. Using the developed informational cognitive model for diagnosing complex technical systems, the method and decision support model allows us to: diagnose the risk values of system component failures when information about component failures is received; to predict system components failure risk value in order to a strategy for their recovery; support decision making when searching for the causes of system component failures. The developed methods and models, the proposed solutions for informatization of diagnostics and prediction of the complex system technical condition provide flexibility and adaptability. | en |
dc.language.iso | en | en |
dc.publisher | RWTH Aachen University | en |
dc.relation.ispartof | CEUR Workshop Proceedings. 2608 : 42-56. | en |
dc.subject | complex technical system | en |
dc.subject | diagnostics | en |
dc.subject | simulation | en |
dc.subject | cognitive model | en |
dc.subject | decision | en |
dc.subject | support | en |
dc.title | Complex technical system condition diagnostics and prediction computerization | en |
dc.type | Article |
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