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Reliability model of sequence motions and its solving idea

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Badanie modelu niezawodności ruchów sekwencyjnych oraz propozycja rozwiązania
Języki publikacji
EN
Abstrakty
EN
The missions of weapon systems are becoming increasingly complex. Thus, more mechanism motions than one are required to complete one mission. Under such conditions, a sort of mission has emerged, that needs a few mechanism motions to be executed in sequence. This means that the mission is not completed until all the motions have been executed successfully in strict sequence. This sequence motion system can be considered as a traditional series system with the motions treated as subsystems. Then, the system reliability can be analyzed with the traditional series system reliability method. However, this method cannot fully reflect the characteristics of a sequence. In this work, a reliability model of sequence motions and its solving idea are proposed. In this reliability model, the influence factors of each motion are included. Particularly, the performance function of the former motion is regarded as just one of the influence factors of the next motion, which is the most significant feature for the sequence motion system. Afterward, a solving idea with characteristics of a gradually shrinking sample space is proposed based on Monte-Carlo simulation. Finally, the reliability model of sequence motions and its solving idea are illustrated with a case study on the automatic chain shell magazine sequence motions of a self-propelled artillery.
PL
Misje systemów uzbrojenia stają się coraz bardziej złożone. Często, jedna misja wymaga wykonania przez układ zmechanizowany więcej niż jednego ruchu. W artykule omówiono misję, w której układ zmechanizowany wykonuje sekwencję kilku ruchów. Misja w takim układzie nie zostanie ukończona, dopóki wszystkie ruchy nie zostaną prawidłowo wykonane w ściśle określonej kolejności. Taki układ sekwencyjnych ruchów można rozważać w kategoriach tradycyjnego systemu szeregowego, traktując poszczególne ruchy jako jego podsystemy. Wówczas, niezawodność systemu można analizować za pomocą tradycyjnej metody analizy niezawodności systemów szeregowych. Jednak, metoda ta nie jest w stanie w pełni odzwierciedlić charakterystyki sekwencji. W niniejszym artykule zaproponowano model niezawodności ruchów sekwencyjnych oraz jego rozwiązanie.
Rocznik
Strony
359--366
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
autor
  • School of Mechanical Engineering and Automation Northeastern University No.11, Alley 3, Wenhua Road, Heping District, Shenyang, China
autor
  • School of Mechanical Engineering and Automation Northeastern University No.11, Alley 3, Wenhua Road, Heping District, Shenyang, China
autor
  • School of Mechanical Engineering and Automation Northeastern University No.11, Alley 3, Wenhua Road, Heping District, Shenyang, China
autor
  • School of Biomedical Engineering Sun Yat-sen University No.132, East Outer Ring Road, Guangzhou University City, Guangzhou, China
Bibliografia
  • 1. Wang G Y. On the development of uncertain structural mechanics. Advances in Mechanics 2002.
  • 2. Asri Y M, Azrulhisham E A, Dzuraidah A W, Shahrir A, Shahrum A, Azami Z. Fatigue life reliability prediction of a stub axle using Monte Carlo simulation. International Journal of Automotive Technology 2011; 12(5): 713-719, https://doi.org/10.1007/s12239-011-0083-z.
  • 3. Bhavajaru M P, Billinton R, Reppen N D, Ringlee N D, Albrecht P F. Requirements for composite system reliability evaluation models. IEEE Transactions on Power Systems 2002; 3(1): 149-157, https://doi.org/10.1109/59.43192.
  • 4. Billinton R, Li W. System state transition sampling method for composite system reliability evaluation. IEEE Transactions on Power Systems 2002; 8(3): 761-770, https://doi.org/10.1109/59.260930.
  • 5. Bucher C G, Bourgund U. A fast and efficient response surface approach for structural reliability problems. Structural Safety 1990; 7(1): 57-66, https://doi.org/10.1016/0167-4730(90)90012-E.
  • 6. Chao M T, Fu J C. The Reliability of a Large Series System under Markov Structure. Advances in Applied Probability 1991; 23(4): 894-908, https://doi.org/10.2307/1427682.
  • 7. Chern M S. On the computational complexity of reliability redundancy allocation in a series system. Operations Research Letters 1992;11(5): 309-315, https://doi.org/10.1016/0167-6377(92)90008-Q.
  • 8. Guan X L, Melchers R E. Effect of response surface parameter variation on structural reliability estimates. Structural Safety 2001; 23(4):429-444, https://doi.org/10.1016/S0167-4730(02)00013-9.
  • 9. Sandler B Z. Probabilistic approach to mechanisms. New York: Elsevier, 1984.
  • 10. Huntington D E, Lyrintzis C S. Nonstationary Random Parametric Vibration in Light Aircraft Landing Gear. Journal of Aircraft 1998; 35(1):145-151, https://doi.org/10.2514/2.2272.
  • 11. Kim J, Song W J, Kang B S. Stochastic approach to kinematic reliability of open-loop mechanism with dimensional tolerance. Applied Mathematical Modelling 2010; 34(5): 1225-1237, https://doi.org/10.1016/j.apm.2009.08.009.
  • 12. Misawa M. Deployment reliability prediction for large satellite antennas driven by spring mechanisms. Journal of Spacecraft & Rockets 2015; 31(5): 878-882.
  • 13. Papadrakakis M, Lagaros N D. Reliability-based structural optimization using neural networks and Monte Carlo simulation. Computer Methods in Applied Mechanics & Engineering 2002; 191(32): 3491-3507, https://doi.org/10.1016/S0045-7825(02)00287-6.
  • 14. Patel J, Choi S K. Classification approach for reliability-based topology optimization using probabilistic neural networks. Structural & Multidisciplinary Optimization 2012; 45(4): 529-543, https://doi.org/10.1007/s00158-011-0711-2.
  • 15. Rao S S, Bhatti P K. Probabilistic approach to manipulator kinematics and dynamics. Reliability Engineering & System Safety 2001; 72(1):47-58, https://doi.org/10.1016/S0951-8320(00)00106-X.
  • 16. Rhyu J H, Kwak B M. Optimal Stochastic Design of Four-Bar Mechanisms for Tolerance and Clearance. Journal of Mechanical Design 1988; 110(3): 255-262.
  • 17. Chern M S. On the computational complexity of reliability redundancy allocation in a series system. Operations Research Letters 1992;11(5): 309-315, https://doi.org/10.1016/0167-6377(92)90008-Q.
  • 18. Santini P, Gasbarri P. Dynamics of multibody systems in space environment; Lagrangian vs. Eulerian approach. Acta Astronautica 2004;54(1): 1-24, https://doi.org/10.1016/S0094-5765(02)00277-1.
  • 19. Sung C S, Cho Y K. Reliability optimization of a series system with multiple-choice and budget constraints. European Journal of Operational Research 2000; 127(1): 159-171, https://doi.org/10.1016/S0377-2217(99)00330-6.
  • 20. Wang S X, Wang Y H, He B Y. Dynamic modeling of flexible multi-body systems with parameter uncertainty. Chaos Solitons & Fractals 2008; 36(3): 605-611, https://doi.org/10.1016/j.chaos.2006.06.091.
  • 21. Zhao Y G, Ono T. Moment methods for structural reliability. Structural Safety 2001; 23(1): 47-75, https://doi.org/10.1016/S0167- 4730(00)00027-8.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3c5e4cd5-4072-45f4-85ca-4ebf42f0def7
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