Smart Structures and Systems

  • 제18권5호
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  • Pages.983-1004
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  • 2016
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Detection of damage in truss structures using Simplified Dolphin Echolocation algorithm based on modal data

  • Kaveh, Ali (Centre of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science and Technology) ;
  • Vaez, Seyed Rohollah Hoseini (Department of Civil Engineering, Faculty of Engineering, University of Qom) ;
  • Hosseini, Pedram (Department of Civil Engineering, Faculty of Engineering, University of Qom) ;
  • Fallah, Narges (Department of Civil Engineering, Faculty of Engineering, University of Qom)
  • 투고 : 2016.01.17
  • 심사 : 2016.06.10
  • 발행 : 2016.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

Nowadays, there are two classes of methods for damage detection in structures consisting of static and dynamic. The dynamic methods are based on studying the changes in structure's dynamic characteristics. The theoretical basis of this method is that damage causes changes in dynamic characteristics of structures. The dynamic methods are divided into two categories: signal based and modal based. The modal based methods utilize the modal properties consisting of natural frequencies, modal damping and mode shapes. As the modal properties are sensitive to changes in the structure, these can be used for detecting the damages. In this study, using dynamic method and modal based approach (natural frequencies and mode shapes), the objective function is formulated. Then, detection of damages of truss structures is addressed by using Simplified Dolphin Echolocation algorithm and solving inverse optimization problem. Many scenarios are used to simulate the damages. To demonstrate the ability of the algorithm, different truss structures with several multiple elements scenarios are tested using a few runs. The influence of the two different levels of noise in the modal data for these scenarios is also considered. The last example of this article is investigated using a different mutation. This mutation obtains the exact answer with fewer loops and population by limited computational effort.

키워드

과제정보

연구 과제 주관 기관 : Iran National Science Foundation

참고문헌

  1. Carden, E.P. and Fanning, P. (2001), "Vibration based condition monitoring: a review", Struct. Health Monit., 3(4), 355-377. https://doi.org/10.1177/1475921704047500
  2. Chen, B. and Nagarajaiah, S. (2013), "Flexibility-based structural damage identification using Gauss? Newton method", Sadhana, 38(4), 557-569. https://doi.org/10.1007/s12046-013-0151-3
  3. Doebling, S.W., Farrar, C., Prime, M.B. and Shevitz, D.W. (1996), Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics a literature review, Los Alamos National Lab, NM, United States.
  4. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Digest, 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  5. Fan, W. and Qiao, P. (2011), "Vibration-based damage identification methods: a review and comparative study", Struct. Health Monit., 10(1), 83-111. https://doi.org/10.1177/1475921710365419
  6. Gandomi, A.H. (2014), "Interior search algorithm (ISA): a novel approach for global optimization", ISA Trans., 53(4), 1168-1183. https://doi.org/10.1016/j.isatra.2014.03.018
  7. Hakim, S.J.S. and Abdul Razak, H. (2013), "Structural damage detection of steel bridge girder using artificial neural networks and finite element models". Steel Compos. Struct., 14(4) , 367-377. https://doi.org/10.12989/scs.2013.14.4.367
  8. hybridized CSS-BBBC algorithm with trap recognition capability", Comput. Struct., 102, 14-27.
  9. Kaveh, A. (2014), "Advances in metaheuristic algorithms for optimal design of structures", Springer International Publishing, Switzerland.
  10. Kaveh, A. and Farhoudi, N. (2013), "A new optimization method: Dolphin echolocation", Adv. Eng. Softw., 59, 53-70. https://doi.org/10.1016/j.advengsoft.2013.03.004
  11. Kaveh, A. and Farhoudi, N. (2016), "Dolphin echolocation optimization: continuous search space", Adv. Comput. Des., 1(2), 175-194. https://doi.org/10.12989/acd.2016.1.2.175
  12. Kaveh, A. and Hosseini, P. (2014), "A simplified dolphin echolocation optimization method for optimum design of trusses", Int. J. Optim. Civil Eng., 4(3), 381-397.
  13. Kaveh, A. and Mahdavi, V. (2016), "Damage Identification of truss structures using CBO and ECBO algorithms", Asian J. Civil Eng. (BHRC), 17(1), 75-89.
  14. Kaveh, A. and Maniat, M. (2014), "Damage detection in skeletal structures based on charged system search optimization using incomplete modal data", Int. J. Civil Eng., IUST, 12(2), 193-200.
  15. Kaveh, A. and Maniat, M. (2015), "Damage detection based on MCSS and PSO using modal data", Smart Struct. Syst., 15(5), 1253-1270. https://doi.org/10.12989/sss.2015.15.5.1253
  16. Kaveh, A. and Zolghadr, A. (2011), "Shape and size optimization of truss structures with frequency constraints using enhanced charged system search algorithm", Asian J. Civil Eng., 12(4), 487-509.
  17. Kaveh, A. and Zolghadr, A. (2012), "Truss optimization with natural frequency constraints using a hybridized CSS-BBBC algorithm with trap recognition capability", Comput. Struct., 102, 14-27.
  18. Kaveh, A. and Zolghadr, A. (2015), "An improved CSS for damage detection of truss structures using changes in natural frequencies and mode shapes", Adv. Eng. Softw., 80, 93-100. https://doi.org/10.1016/j.advengsoft.2014.09.010
  19. Kim, N., Kim, H. and Lee, J. (2014), "Damage detection of truss structures using two-stage optimization based on micro genetic algorithm", J. Mech. Sci. Technol., 28(9), 3687-3695. https://doi.org/10.1007/s12206-014-0830-y
  20. Konzelman, C.J. (1986), Dual methods and approximation concepts for structural optimization.
  21. Kwon, Y.W. and Bang, H. (2000), The finite element method using MATLAB, CRC Press.
  22. Lingyun, W. et al. (2005), "Truss optimization on shape and sizing with frequency constraints based on genetic algorithm", Comput. Mech., 35(5), 361-368. https://doi.org/10.1007/s00466-004-0623-8
  23. Majumdar, A., Maiti, D.K. and Maity, D. (2012), "Damage assessment of truss structures from changes in natural frequencies using ant colony optimization", Appl. Math. Comput., 218(19), 9759-9772.
  24. Pan C.D., Yu L., Chen Z.P., Luo W.F. and Liu H.L. (2016). "A hybrid self-adaptive Firefly-Nelder-Mead algorithm for structural damage detection". Smart Struct. Syst., An Int'l Journal, 17(6), 957-980. https://doi.org/10.12989/sss.2016.17.6.957
  25. Pholdee, N. and Bureerat, S. (2014), "Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints", Adv. Eng. Softw., 75, 1-13. https://doi.org/10.1016/j.advengsoft.2014.04.005
  26. Sedaghati, R. (2005), "Benchmark case studies in structural design optimization using the force method", Int. J. Solids Struct., 42(21), 5848-5871. https://doi.org/10.1016/j.ijsolstr.2005.03.030
  27. Sohn, H. et al. (2004), A review of structural health monitoring literature: 1996-2001, Los Alamos National Lab, NM, United States.
  28. Villalba-Morales, J.D. and Laier, D.K. (2014), "Assessing the performance of a differential evolution algorithm in structural damage detection by varying the objective function", Dyna, 81(188), 106-115. https://doi.org/10.15446/dyna.v81n188.41105
  29. Villalba, J. and Laier, J.E. (2012), "Localising and quantifying damage by means of a multi-chromosome genetic algorithm", Adv. Eng. Softw., 50, 150-157. https://doi.org/10.1016/j.advengsoft.2012.02.002

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