Integration of uniform design and quantum-behaved particle swarm optimization to the robust design for a railway vehicle suspension system under different wheel conicities and wheel rolling radii 
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期刊名称Acta Mechanica Sinica
作者Yung-Chang Cheng; Cheng-Kang Lee
栏目DYNAMICS, VIBRATION, AND CONTROL
摘要This paper proposes a systematic method, integrating the uniform design (UD) of experiments and quantum-behaved particle swarm optimization (QPSO), to solve the problem of a robust design for a railway vehicle suspension system. Based on the new nonlinear creep model derived from combining Hertz contact theory, Kalker's linear theory and a heuristic nonlinear creep model, the modeling and dynamic analysis of a 24 degree-of-freedom railway vehicle system were investigated. The Lyapunov indirect method was used to examine the effects of suspension parameters, wheel conicities and wheel rolling radii on critical hunting speeds. Generally, the critical hunting speeds of a vehicle system resulting from worn wheels with different wheel rolling radii are lower than those of a vehicle system having original wheels without different wheel rolling radii. Because of worn wheels, the critical hunting speed of a running railway vehicle substantially declines over the long term. For safety reasons, it is necessary to design the suspension system parameters to increase the robustness of the system and decrease the sensitive of wheel noises. By applying UD and QPSO, the nominal-the-best signal-to-noise ratio of the system was increased from -48.17 to -34.05 dB. The rate of improvement was 29.31%. This study has demonstrated that the integration of UD and QPSO can successfully reveal the optimal solution of suspension parameters for solving the robust design problem of a railway vehicle suspension system.
英文栏目名称DYNAMICS, VIBRATION, AND CONTROL
关键词Speed-dependent nonlinear creep model; Quantum-behaved particle swarm optimization; Uniform design; Wheel rolling radius; Hunting stability
参考文献1. Zeng, X.H., Wu, H., Lai, J., et al.: Hunting stability of high-speed railway vehicles on a curved track considering the effects of steady aerodynamic loads. J. Vib. Control 22, 4159-4175 (2016)
2. Zeng, X.H., Wu, H., Lai, J., et al.: Influences of aerodynamic loads on hunting stability of high-speed railway vehicles and parameter studies. Acta Mech. Sin. 30, 889-900 (2014)
3. Molatefi, H., Hecht, M., Kadivar, M.H.: Critical speed and limit cycles in the empty y25-freight wagon. Proc. Inst. Mech. Eng. Part F: J. Rail Rapid Transit 220, 347-359 (2006)
4. Wang, K.Y., Liu, P.F.: Lateral stability analysis of heavy-haul vehicle on curved track based on wheel/rail coupled dynamics. J. Transp. Technol. 2, 150-157 (2012)
5. Kim, P., Seok, J.: Bifurcation analysis on the hunting behavior of a dual-bogie railway vehicle using the method of multiple scales. J. Sound Vib. 329, 4017-4039 (2010)
6. Karim, H., Ali, A., Rasheed, A.K.: Investigation to improve hunting stability of railway carriage using semi-active longitudinal primary stiffness suspension. J. Mech. Eng. Res. 2, 97-105 (2010)
7. Michal, M., Michael, H.: Effects of speed, load and damping on the dynamic response of railway bridges and vehicles. Comput. Struct. 86, 556-572 (2008)
8. Ranjbar,M.,Ghazavi,M.R.: Lateral stability analysis of high-speed railway vehicle on curve. In: Proceeding of International Conference on Advances in Robotic, Mechanical Engineering and Design, Chandigarh, 11-14 (2012)
9. Gao, X.J., Li, Y.H., Yue, Y., et al.: Symmetric/asymmetric bifurcation behaviours of a bogie system. J. Sound Vib. 332, 936-951 (2013)
10. Molatefi, H., Hecht, M., Kadivar, M.H.: Effect of suspension system in the lateral stability of railway freight trucks. Proc. Inst. Mech. Eng. Part F: J. Rail Rapid Transit 221, 399-407 (2007)
11. Piotrowski, J., Kik, W.: A simplified model of wheel/rail contact mechanics for non-hertzian problems and its application in rail vehicle dynamic simulations. Veh. Syst. Dyn. 46, 27-48 (2008)
12. Pombo, J., Ambrósio, J., Silva, M.: A new wheel-rail contact model for railway dynamics. Veh. Syst. Dyn. 45, 165-189 (2007)
13. Polach, O.: On non-linear methods of bogie stability assessment using computer simulations. Proc. Inst. Mech. Eng. Part F J. Rail Rapid Transit 220, 13-27 (2006)
14. Kovalev, R., Yazykov, V.N., Mikhalchenko, G.S., et al.: Railway vehicle dynamics: some aspects of wheel-rail contact modeling and optimization of running gears. Mech. Based Des. Struct. Mach. 31, 315-334 (2003)
15. Shen, G., Zhong, X.: A design method for wheel profiles according to the rolling radius difference function. Proc. Inst. Mech. Eng. Part F J. Rail Rapid Transit 225, 457-462 (2011)
16. Sun, S., Li, L., Zhou, J., et al.: Influence of wheel diameter difference on safety and stationarity of vehicles crawling over the curved bridge. Appl. Mech. Mater. 209-211, 2117-2120 (2012)
17. He, Y., McPhee, J.: Optimization of the lateral stability of rail vehicles. Veh. Syst. Dyn. 38, 361-390 (2002)
18. He, Y., McPhee, J.: Optimization of curving performance of rail vehicles. Veh. Syst. Dyn. 43, 859-923 (2005)
19. Sayyaadi, H., Shokouhi, N.: New dynamics model for rail vehicles and optimizing air suspension parameters using GA. Sci. Iran. 16, 496-512 (2009)
20. Wu, Q., Cole, C., McSweeney, T.: Applications of particle swarm optimization in the railway domain. Int. J. Rail Transp. 4, 167-190 (2016)
21. Cheng, Y.C., Lee, C.K.: Robust design of suspension parameters for high speed railway vehicle based on uniform design and kriging interpolation. Int. J. Adv. Mechatron. Syst. 3, 268-278 (2011)
22. Lee, C.K., Cheng, Y.C.: Application of uniform design and quantum-behaved particle swarm optimization in solving the sensitivity problem a railway vehicle system. Procedia Eng. 79, 4227-4436 (2014)
23. Nejlaoui, M., Houidi, A., Affi, Z., et al.: Multiobjective robust design optimization of rail vehicle moving in short radius curved tracks based on the safety and comfort criteria. Simul. Model. Pract. Theory 30, 21-34 (2013)
24. Lee, K.K., Park, C.K., Han, S.H.: Robust design of railway vehicle suspension using a process capability index. J. Mech. Sci. Technol. 24, 215-218 (2010)
25. Cheng, Y.C.: Hunting stability analysis of a railway vehicle system using a novel non-linear creep model. Proc. Inst. Mech. Eng. Part F J. Rail Rapid Transit 226, 612-629 (2012)
26. Vidyasager, M.: Nonlinear Systems Analysis. Prentice-Hall Press, Hyderabad (1978)
27. Garg, V.K., Dukkipati, R.V.: Dynamics of Railway Vehicle Systems. Academic Press, Orlanda (1984)
28. Adachi, M., Terumichi, Y., Suda, Y., et al.: Analysis on wheel load variation in coupled motion between wheel and track. Trans. Jpn. Soc. Mech. Eng. Ser. C 73, 748-755 (2007)
29. Ahmed, A.K.W., Sankar, S.: Lateral stability behavior of railway freight car system with elasto-damper coupled wheelset: part 2— truck model. Trans. ASME J. Mech. Transm. Autom. Des. 109, 500-507 (1987)
30. John, A.R.: Mathematical Statistics and Data Analysis, 2nd edn. Duxbury Press, Belmont (1994)
31. Fang, K.T., Wang, Y.: Number-Theoretic Methods in Statistics. Chapman & Hall Press, London (1994)
32. Wang, J.M., Lan, S., Li, W.K.: Numerical simulation and process optimization of an aluminum holding furnace based on response surface methodology and uniform design. Energy 72, 521-535 (2014)
33. Li, D.J., Song, J.F., Xu, A.Q., et al.: Optimization of the ultrasoundassisted synthesis of lutein disuccinate using uniform design. Ultrason. Sonochem. 21, 98-103 (2014)
34. Dai, C., Wang, Y.: A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization. Appl. Soft Comput. J. 30, 238-248 (2015)
35. Voratas, K.: Comparison of three evolutionary algorithms: GA, PSO, and DE. Ind. Eng. Manag. Syst. 11, 215-223 (2012)
36. Sun, J., Feng, B.,Xu,W.: Particle swarm optimizationwith particles having quantum behavior. IEEE Congr. Evol. Comput. 1, 325-331 (2004)
37. Sun, J., Wu, X., Palade, V., et al.: Convergence analysis and improvements of quantum-behaved particle swarm optimization. Inf. Sci. 193, 81-103 (2012)
38. Clerc, M., Kennedy, J.: The particle swarm: explosion, stability, and convergence in a multi-dimensional complex space. IEEE Trans. Evol. Comput. 6, 58-73 (2002)
39. Sun, J., Xu, W., Feng, B.: A global search strategy of quantumbehaved particle swarm optimization. IEEE Conf. Cybern. Intell. Syst. 1, 111-116 (2004)
2017
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开始页码963
结束页码980
DOI10.1007/s10409-017-0658-7
点击率44
作者地址1 Department of Mechanical and Automation Engineering, Kaohsiung First University of Science and Technology, Kaohsiung 811, Taiwan, China;
2 Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung 833, Taiwan, China

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