Abstract
A model complex and algorithms for assessing the technical condition (TC) and reliability of the launch vehicle (LV) “Soyuz-2” with the decision support (DS) for managing its life cycle (LC) is considered in the article. On the basis of the analysis of modern problems and the requirements for the efficiency, quality and reliability of the assessment of the LV and the reliability of LV, it was concluded that it is necessary to use the new intelligent information technology (IIT), presented in the article, when designing the automated monitoring systems of the condition and DS for managing the LC LV “Soyuz-2”. As a theoretical basis for this technology, the modification of the generalized computational model (GCM) as a knowledge representation model, allowing to build simulation-analytical model-based complexes for monitoring conditions and managing complex organizational and technical objects (COTO), is considered.
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Acknowledgments
The research described in this paper is partially supported by the Russian Foundation for Basic Research (grants 16-07-00779, 16-08-00510, 16-08-01277, 16-29-09482-ofi-i, 17-08-00797, 17-06-00108, 17-01-00139, 17-29-07073-ofi-i), grant 074-U01 (ITMO University), project 6.1.1 (Peter the Great St. Petersburg Politechnic University) supported by Government of Russian Federation, Program STC of Union State “Technology-SG” (project 1.3.3.3.1), state order of the Ministry of Education and Science of the Russian Federation № 2.3135.2017/4.6, state order of the Ministry of Education and Science of the Russian Federation № 2.3135.2017/4.6, state research 0073–2014–0009, 0073–2015–0007, International project ERASMUS +, Capacity building in higher education, № 73751-EPP-1-2016-1-DE-EPPKA2-CBHE-JP, International project KS1309 InnoForestView Innovative information technologies for analyses of negative impact on the cross-border region forests.
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Bakhmut, A.D. et al. (2019). Models, Algorithms and Monitoring System of the Technical Condition of the Launch Vehicle “Soyuz-2” at All Stages of Its Life Cycle. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_28
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