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Automated Logical-Probabilistic Methodology and Software Tool as Component of the Complex of Methodologies and Software Tools for Evaluation of Reliability and Survivability of Onboard Equipment of Small Satellites

  • Vadim Skobtsov
  • Natalia Lapitskaja
  • Roman Saksonov
  • Semyon Potryasaev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 763)

Abstract

The paper presents solutions for current problems with estimation and analysis of indicators of reliability and survivability in onboard equipment (OE) of small satellites (SS) based on the logical-probabilistic approach to the reliability and survivability estimation of complex systems. There were developed modified logical-probabilistic method and software tool for evaluating the reliability and survivability of OE SS systems. The correctness of suggested method and software tool was shown by computational experiments on some systems of OE SS similar to Belarusian SS, later compared with “Arbitr” software complex results. The software tool was integrated into the complex of methodologies and software tools for evaluation, analysis and prediction of the values of reliability and survivability indicators of OE SS in local desktop and distributed web versions.

Keywords

Logical-probabilistic method Reliability Survivability Onboard equipment for small satellites Diagram of functional integrity System operability function Probability of failure-free operation Software tool 

Notes

Acknowledgments

The research described in Sect. 2 of paper is supported by project No. 17-11-01254 of Russian Science Foundation, the research described in Sect. 3 of paper is supported by the state research 0073–2018–0003. All represented in paper research results were supported by Program STC of Union State “Monitoring-SG” (project 6MCГ/13-224-2, the Belarusian side).

References

  1. 1.
    Mozhaev, A.S.: The technology of automated structural and logical modeling of reliability, survivability, safety, efficiency and risk of functioning the systems. Instrum. Syst. Monit. Control Diagn. N9, 1–14 (2008). (in Russian)Google Scholar
  2. 2.
    Mozhaev, A.S., Grommov, V.N.: Theoretical foundations of the general logical-probabilistic method of automated systems modeling. SPb, VITU (2000)Google Scholar
  3. 3.
    Skobtsov, V., Novoselova, N., Arhipov, V., Potryasaev, S.: Intelligent telemetry data analysis of small satellites. In: Kacprzyk, J., et al. (eds.) Proceedings of the 6th Computer Science On-line Conference 2017 (CSOC2017), vol. 2 in Advances in Intelligent Systems and Computing, vol. 574, pp. 351–361. Springer International Publishing Switzerland (2017)Google Scholar
  4. 4.
    Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 3rd edn. The MIT Press, Cambridge (2009)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Vadim Skobtsov
    • 1
  • Natalia Lapitskaja
    • 2
  • Roman Saksonov
    • 3
  • Semyon Potryasaev
    • 4
  1. 1.United Institute of Informatics Problems, National Academy of Sciences of BelarusMinskBelarus
  2. 2.Belarusian State University of Informatics and RadioelectronicsMinskBelarus
  3. 3.Geoinformation SystemsMinskBelarus
  4. 4.St. Petersburg Institute of Informatics and Automation, Russian Academy of Sciences (SPIIRAS)St. PetersburgRussia

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