A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

Advances in Engineering Software

Volumn 40, Issue 9, 2009, Pages 883-891

  Begambre, O ^a,b   Laier, J E ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b UNIVERSIDAD INDUSTRIAL DE SANTANDER   (Colombia)

Author keywords

Cracked beam; Damage identification; Inverse problems; Non linear oscillator; Particle Swarm Optimization; Truss structure

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DAMAGE DETECTION; DIFFERENTIAL EQUATIONS; FREQUENCY RESPONSE; HEURISTIC ALGORITHMS; HEURISTIC METHODS; IDENTIFICATION (CONTROL SYSTEMS); INVERSE PROBLEMS; OPTICAL COMMUNICATION; OSCILLATORS (MECHANICAL); PHOTOACOUSTIC EFFECT; SIMULATED ANNEALING; STRUCTURAL ANALYSIS; STRUCTURAL OPTIMIZATION; TRUSSES;

BAR TRUSS; BENCHMARK FUNCTIONS; CRACKED BEAM; DAMAGE IDENTIFICATION; DAMAGE LOCATIONS; DUFFING OSCILLATORS; FINITE ELEMENTS; FREE-FREE BEAMS; FREQUENCY-DOMAIN DATUM; FREQUENCY-RESPONSE FUNCTIONS; HYBRID METHODS; HYBRID PARTICLE SWARM OPTIMIZATIONS; INCOMPLETE DATUM; MINIMIZATION PROBLEMS; MODEL-BASED; NELDER-MEAD ALGORITHMS; NON-LINEAR OSCILLATOR; NOVEL STRATEGIES; OBJECTIVE FUNCTIONS; SIMPLEX ALGORITHMS; SIMPLEX METHODS; STRUCTURAL DAMAGE IDENTIFICATIONS; TRUSS STRUCTURE;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 67349114407     PISSN: 09659978     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advengsoft.2009.01.004     Document Type: Article

References (35)

1. Begambre O., and Laier J.E. Structural damage identification using Particle Swarm Optimization. In: Topping B.H.V., Montero G., and Montenegro R. (Eds). Proceedings of the fifth international conference on engineering computational technology (2006), Civil-Comp Press, Stirlingshire, United Kingdom paper 41
2. Zou Y., Tong L., and Steven P. Vibration-based model-dependent damage (delamination) identification and health monitoring for composite structures: a review. J Sound Vib 230 (2000) 357-378
3. Fang X., Luo H., and Tang J. Structural damage detection using neural network with learning rate improvement. Comput Struct 83 (2005) 2150-2161
4. Worden K., Sohn H., and Farrar C.R. Novelty detection in a changing environment: regression and interpolation approaches. J Sound Vib 258 4 (2002) 741-761
5. Goch G., Schmitz B., Karpuschewski B., Geerkens J., Reigl M., Sprongl P., et al. Review of non-destructive measuring methods for the assessment of surface integrity: a survey of new measuring methods for coatings, layered structures and processed surfaces. Precis Eng 23 (1999) 9-33
6. Worden K., and Dulieu-Barton J.M. An overview of intelligent fault detection in systems and structures. Struct Health Monitor 3 1 (2004) 85-98
7. Gladwell G.M.L. Inverse problems in vibration. Appl Mech Rev 49 (1996) 525-534
8. Lee J.J., Lee J.W., Yi J.H., Yu C.B., and Jung H.I. Neural networks-based damage detection for bridges considering errors in baseline finite element models. J Sound Vib 280 (2005) 555-578
9. Worden K. Structural fault detection using a novelty measure. J Sound Vib 201 1 (1997) 85-101
10. Rao M.A., Srinivas J., and Murthy B.S.N. Damage detection in vibrating bodies using genetic algorithms. Comput Struct 82 (2004) 963-968
11. Kaazem M., and Nafaspour R. Structural damage detection by genetic algorithms. AIAA J 40 7 (2002) 1395-1401
12. Kwon K.-S., and Lin R.-M. Robust finite element model updating using Taguchi method. J Sound Vib 280 1-2 (2005) 77-99
13. Doebling S.W., Farrar C.R., and Prime M.B. A Summary review of vibration-based damage identification methods. Shock Vib Digest 30 2 (1998) 91-105
14. Kim J.-T., Ryu Y.-S., Cho H.-M., and Stubbs N. Damage identification in beam-type structures: frequency-based methods vs. mode-shape-based methods. Eng Struct 25 (2003) 57-67
15. Sinha J.K., Friswell M.I., and Edwards S. Simplified models for the locations of cracks in beam structures using measured vibration data. J Sound Vib 251 1 (2002) 13-38
16. Saavedra P.N., and Cuitiño L.A. Crack detection and vibration behavior of cracked beams. Comput Struct 79 (2001) 1451-1459
17. Parsopoulos K.E., and Vrahatis M.N. Recent approaches to global optimization problems through particle swarm optimization. Nat Comput 1 (2002) 235-306
18. Storm R., and Price K. Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces. J Global Optimiz 11 (1997) 341-359
19. Nelder J.A., and Mead R. A Simplex method for function minimization. Comput J 7 (1965) 308-313
20. Lagarias J.C., Redds J.A., Wright M.H., and Wrigth P.E. Convergence properties of the Nealder-Mead Simplex method in low dimensions. SIAM J Optimiz 9 1 (1998) 112-147
21. Kennedy J, Eberhart R. Particle swarm optimization. In: Proceedings of the 1995 IEEE international conference on neural networks, vol. 4, 1995. p. 1942-8.
22. Kennedy J. The Particle Swarm: social adaptation of knowledge. In: Proceedings of the 1997 IEEE international conference on evolutionary computation, 1997. p. 303-8.
23. Alrashidi M.R., and El-Hawary M.E. A survey of particle swarm optimization applications in power system operations. Electric Power Compon Syst 34 12 (2006) 1349-1357
24. Wetter M., and Wright J. A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization. Build Environ 39 (2004) 989-999
25. Venter G., and Sobieszczanski-sobieski J. Particle swarm optimization. AIAA J 41 8 (2003) 1583-1589
26. Schutte J.F., and Groenwold A.A. Sizing design of truss structures using particle swarms. Struct Multidiscip Optimiz 25 (2003) 261-269
27. Fourie P.C., and Groenwold A.A. The particle swarm optimization algorithm in size and shape optimization. Struct Multidiscip Optimiz 23 4 (2002) 259-267
28. Chau K.W. Algal bloom prediction with particle swarm optimization algorithm. Lect Notes Artif Intell 3801 (2005) 645-650
29. Chau K.W. Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River. J Hydrol 329 3-4 (2006) ; 363-367
30. Shi Y., and Eberhart R.C. Parameter selection in particle swarm optimization. In: Porto V.W., Saravanan N., Waagen D., and Eiben A.E. (Eds). Evolutionary programming VII. Lecture notes in computer science (1998), Springer, Berlin 591-600
31. Tayal M. Particle Swarm Optimization for mechanical design. Master thesis, University of Texas at Arlington, 2003.
32. Atalla MJ. Model updating using neural networks. PhD thesis, Virginia Polytechnic Institute and State University, 1996.
33. Corana A., Marchesi M., Martini C., and Ridella S. Minimizing multimodal functions of continuous variables with the simulated annealing algorithm. ACM Trans Math Software 13 3 (1987) 262-280
34. Goffe W.L., Ferrier G.D., and Rogers J. Global optimization of statistical functions with simulated annealing. J Econom 60 (1994) 65-99
35. Nayfehl A.H., and Mook D.T. Non-linear oscillations (1979), John Wiley and Sons, New York