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Contribution to random vibration numerical simulation and optimisation of nonlinear mechanical systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study considered the solution of the stochastic vibration of non-linear mechanical systems with Gaussian random excitations. It realised a short review of linearisations techniques in stochastic dynamics mainly with application in the area of truss finite element modelling. The presented method of statistical linearisation is applied to numerical testing. In the second part of the article, the sensitivity analysis of the first two stress statistical moments and structural weight minimising subjected to the random stress constrains presented by mean value and standard deviation was brought to the fore. Cross-sectional areas were used as optimising parameters.
Rocznik
Tom
Strony
143--154
Opis fizyczny
Bibliogr. 27 poz.
Twórcy
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitná 1, 010 26 Žilina, Slovakia
Bibliografia
  • 1. Bendat Julius S. 1990. Nonlinear system analysis and identification from random data. New York: John Wiley & Sons.
  • 2. Brepta Rudolf, Ladislav Půst, František Turek. 1994. Mechanical vibration. Technical handbook. Praha: Sobotáles.
  • 3. Cherng Rwey-Hua., Wen Yi-Kwei. 1991. „Stochastic finite element analysis of non-linear plane trusses”. Int. Journal Non-Linear Mechanics 26(6): 835-849.
  • 4. Dekýš Vladimír, Alžbeta Sapietová, Ondrej Števka. 2014. „Understanding of the dynamical properties of machines based on the interpretation of spectral measurements and FRF”. Experimental stress analysis 51. Applied Mech. and Materials 486: 106-112.
  • 5. Dobiáš Ivan. 1988. Nonlinear dynamic systems with random inputs. Praha: Academia.
  • 6. Dodok Tomáš, Nadežda Čuboňová, Miroslav Císar, Ivan Kuric, Ivan Zajačko. 2017. „Utilization of strategies to generate and optimize machining sequences in CAD/CAM”. Procedia Engineering 192: 113-118. ISSN 1877-7058.
  • 7. Elishakoff Isaac, Pierluigi Colombi. 1993. „Successful combination of the stochastic linearization and Monte Carlo methods”. J. of Sound and Vibration 160(3): 554-558.
  • 8. Frankovský Peter, Darina Hroncová, Ingrid Delyová, Peter Hudák. 2012. „Inverse and forward dynamic analysis of two link manipulator”. Procedia Engineering 48: 158-163.
  • 9. Flizikowski Jozef, Marek Macko, Jacek Czerniak., Adam Mroziński. 2011. „Implementation of genetic algorithms into development of mechatronic multi-edge's grinder design”, In ASME 2011 International Mechanical Engineering Congress and Exposition, IMECE. Nov. 11-17, 2011, Denver, Colorado, USA.
  • 10. Gerlici Juraj, Tomáš Lack. 2014. „Modified HHT Method for vehicle vibration analysis in time domain utilisation”. Applied Mechanics and Materials 486: 396-405.
  • 11. Homišin Jaroslav, Robert Grega, Peter Kaššay, Gabriel Fedorko, Vieroslav Molnár. 2019. “Removal of systematic failure of belt conveyor drive by reducing vibrations”. Engineering Failure Analysis 99: 192-202. ISSN 1350-6307.
  • 12. Kazakov Igor J. 1983. Analysis of the stochastic system in the space of states. Moskow: Nauka.
  • 13. Krawiec Piotr, Grzegorz Domek, Łukasz Warguła, Konrad Waluś, Jarosław Adamiec. 2018. „The application of the optical system ATOS II for rapid prototyping methods of non-classical models of cogbelt pulleys”. MATEC Web of Conferences 157 (01010).
  • 14. Kropáč Oldřich. 1987. Random effects in mechanical systems. Prague: SNTL.
  • 15. Mazurkiewicz D. 2010. „Tests of extendability and strength of adhesive-sealed joints in the context of developing a computer system for monitoring the condition of belt joints during conveyor operation”. Eksploatacja i Niezawodnosc – Maintenance and Reliability 3: 34-39.
  • 16. Nigam N.C. 1983. Introduction to Random Vibrations. Cambridge : MIT Press.
  • 17. Olsen Gregory R., Vanderplaats Garret N. 1989. „Method for Nonlinear Optimization with Discrete Design Variables”. AIAA Journal 27(11): 1584-1589.
  • 18. Roberts John B., Pol D. Spanos. 1990. Random Vibrations and Statistical Linearization. New York: John Wiley & Sons.
  • 19. Shinozuka Masanobu. 1972. „Monte Carlo simulation of structural dynamics”. Computer and Structures 2: 865-874.
  • 20. Smutny J., V. Nohal, D. Vukusicova, H. Seelmann. 2018. “Vibration analysis by the Wigner-Ville transformation method”. Komunikacie 4. ISSN: 1335-4205.
  • 21. Soong T.T., M. Grigoriu. 1993. Random Vibration of Mechanical and Structural Systems. Prentice-Hall: Englewood Cliffs.
  • 22. Spanos Pol D., M.G. Donley. 1991. „Equivalent statistical quadratization for nonlinear systems”. Journal of Engineering Mechanics ASCE 117: 1289-1309.
  • 23. Spanos Pol D. 1981. „Stochastic linearization in structural dynamics”. Applied Mechanics Reviews 34(1): 1-8.
  • 24. To Cho W.S. 2000. Nonlinear Random Vibration: Analytical Techniques and Applications. Lise, Netherlands: Swets & Zeitlinger B.V.
  • 25. Turygin Yuri, Pavol Božek, Ivan V. Abramov, Yury R. Nikitin. 2018. „Reliability determination and diagnostics of a mechatronic system”. Advances in Science and Technology Research Journal 12(2): 274-290.
  • 26. Wen Y.K. 1989. „Methods of random vibration for inelastic structures”. Applied Mechanics Reviews 42: 39-52.
  • 27. Zul'ová L., R. Grega, J. Krajňák. 2017. „Optimization of noisiness of mechanical system by using a pneumatic tuner during a failure of piston machine”. Engineering Failure Analysis 79: 845-851. ISSN 1350-6307.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-334e86e5-30e6-4856-aed9-91ecbba7d201
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