DOI QR코드

DOI QR Code

Multi-criteria shape design of crane-hook taking account of estimated load condition

  • Muromaki, Takao (Mechanical Engineering, Maizuru National College of Technology) ;
  • Hanahara, Kazuyuki (Graduate School of System Informatics, Kobe University) ;
  • Tada, Yukio (Graduate School of System Informatics, Kobe University)
  • 투고 : 2012.05.01
  • 심사 : 2014.05.18
  • 발행 : 2014.09.10

초록

In order to improve the crane-hook's performance and service life, we formulate a multi-criteria shape design problem considering practical conditions. The structural weight, the displacement at specified points and the induced matrix norm of stiffness matrix are adopted as the evaluation items to be minimized. The heights and widths of cross-section are chosen as the design variables. The design variables are expressed in terms of shape functions based on the Gaussian function. For this multi-objective optimization problem with three items, we utilize a multi-objective evolutionary algorithm, that is, the multi-objective Particle Swarm Optimization (MOPSO). As a common feature of obtained solutions, the side views are tapered shapes similar to those of actual crane-hook designs. The evaluation item values of the obtained designs demonstrate importance of the present optimization as well as the feasibility of the proposed optimal design approach.

키워드

참고문헌

  1. Behera, S.K. and Choukiker, Y. (2010), "Design and optimization of dual band microstrip antenna using particle swarm optimization technique", J. Infrar. Milli. Terahz .Wave., 31, 1346-1354. https://doi.org/10.1007/s10762-010-9722-0
  2. Boyd, J.P. and Wang, L. (2009), "An analytic approximation to the cardinal functions of Gaussian radial basis functions on an infinite lattice", Appl. Math. Comput., 215(6), 2215-2223. https://doi.org/10.1016/j.amc.2009.08.037
  3. Chris, P.P. and Sara, G. (2001), "Comparison of fuzzy set and convex model theories in structural design", Mech. Syst. Sig. Pr., 15(3), 499-511. https://doi.org/10.1006/mssp.2000.1379
  4. Crisfield, M.A. (1991), Non-linear Finite Element Analysis of Solids and Structure: Volume 1, John Wiley & Sons.
  5. Fieldsend, J.E. and Singh, S. (2002), "A multi-objective algorithm based upon particle swarm optimization, an efficient data structure and turbulence", The 2002 U.K. Workshop on Computational Intelligence, 34-44.
  6. Iman, P., Reza, S. and Mansour, S. (2002), "RBF neural network based PI pitch controller for a class of 5-MW wind turbines using particle swarm optimization algorithm", ISA Tran., 51(5), 641-648.
  7. Lam, H.F. and Ng, C.T. (2009), "The selection of pattern features for structural damage detection using an extended Bayesian ANN algorithm", Eng. Struct., 30(10), 2762-2770.
  8. Marano, G.C., Greco, R. and Sgobba, S. (2010), "A comparison between different robust optimum design approaches: Application to tuned mass damper", Probab. Eng. Mech., 25(1), 108-118. https://doi.org/10.1016/j.probengmech.2009.08.004
  9. Ravagnani, M.A.S.S., Silva, A.P., Biscaia , Jr. E.C. and Caballero, J.A. (2009), "Optimal design of shelland-tube heat exchangers using particle swarm optimization", Ind. Eng. Chem. Res., 48, 2927-2935. https://doi.org/10.1021/ie800728n
  10. Mostaghim, S. and Teich, J. (2003), "Strategies for finding good local guides in Multi-objective Particle Swarm Optimization (MOPSO)", IEEE 2003 Swarm Intelligence Symposium, 26-33.
  11. Muromaki, T., Hanahara, K., Tada, Y. and Nishimura, T. (2012), "Estimation of loading conditions of failed crane-hook: an image-based approach with knowledge and simulation", Int. J. Reliab. Saf., 6(1/2/3), 130-147. https://doi.org/10.1504/IJRS.2012.044304
  12. Owen, D.R.J. and Hinton, E. (1980), Finite Elements in Plasticity: Theory and Practice, Pineridge Press Limited, Chapter 5.
  13. Roger, A.H. and Charles, R.J. (1985), Matrix Analysis, Cambridge University Press.
  14. Srirat, J., Kitayama, S. and Yamazaki, K. (2012), "Optimization of initial blank shape with a variable blank holder force in deep-drawing via sequential approximate optimization", J. Adv. Mech. Des., Syst., Manuf., 6(7), 1093-1106. https://doi.org/10.1299/jamdsm.6.1093
  15. Vanderplaats, G.N. (1979), "Efficient algorithm for numerical airfoil optimization", J. Aircraft, 16, 842-847 https://doi.org/10.2514/3.49805
  16. Vissarion, P. and Nikos, D.L. (2009), "Vulnerability-based robust design optimization of imperfect shell structures", Struct. Saf., 31(6), 475-482. https://doi.org/10.1016/j.strusafe.2009.06.006
  17. Xiang, H.J. and Shi, Z.F. (2011), "Vibration attenuation in periodic composite Timoshenko beams on Pasternak foundation", Struct. Eng. Mech., 40(3), 373-392. https://doi.org/10.12989/sem.2011.40.3.373
  18. Zipping, Q., Yuying, X. and Jialing, Y. (2007), "The static displacement and the stress analysis of structures with bounded uncertainties using the vertex solution theorem", Comput. Method. Appl. Mech. Eng., 196, 4965-4984. https://doi.org/10.1016/j.cma.2007.06.022