Structural Engineering and Mechanics

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Structural damage detection based on MAC flexibility and frequency using moth-flame algorithm

  • Ghannadi, Parsa (Department of Civil Engineering, Ahar Branch, Islamic Azad University) ;
  • Kourehli, Seyed Sina (Department of Civil Engineering, Ahar Branch, Islamic Azad University)
  • Received : 2018.10.05
  • Accepted : 2019.03.16
  • Published : 2019.06.25
⟨ Previous Next ⟩

Abstract

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

Keywords

References

  1. Abdo, M.A.B. (2002), "A numerical study of structural damage detection using changes in the rotation of mode shapes", J. Sound Vib., 251(2), 227-239. https://doi.org/10.1006/jsvi.2001.3989
  2. Bureerat, S. and Pholdee, N. (2018), "Inverse problem based differential evolution for efficient structural health monitoring of trusses", Appl. Soft Comput., 66, 462-472. https://doi.org/10.1016/j.asoc.2018.02.046.
  3. Bozorg-Haddad, O. (2018), Advanced Optimization by Nature-Inspired Algorithms, Springer, Singapore. http://doi.org/10.1007/978-981-10-5221-7.
  4. Dinh-Cong, D., Vo-Duy, T. and Nguyen-Thoi, T. (2018a), "Damage assessment in truss structures with limited sensors using a two- stage method and model reduction", Appl. Soft Comput., 66, 264-277. https://doi.org/10.1016/j.asoc.2018.02.028.
  5. Dinh-Cong, D., Ho-Huu, V., Vo-Duy, T., Ngo-Thi, H.Q., Nguyen Thoi, T. (2018b), "Efficiency of Jaya algorithm for solving the optimization-based structural damage identification problem based on a hybrid objective function", Eng. Opt., 50(8), 1233-1251. https://doi.org/10.1080/0305215X.2017.1367392
  6. Eftekhar Azam, S., Mariani, S. and Attari, N. K. A. (2017), "Online damage detection via a synergy of proper orthogonal decomposition and recursive Bayesian filters", Nonlinear Dynam., 89(2), 1489-1511. https://doi.org/10.1007/s11071-017-3530-1
  7. Eftekhar Azam, S. and Mariani, S. (2018), "Online damage detection in structural systems via dynamic inverse analysis: A recursive Bayesian approach", Eng. Struct., 159, 28-45. https://doi.org/10.1016/j.engstruct.2017.12.031.
  8. Eftekhar Azam, S., Rageh, A. and Linzell, D. (2019), "Damage detection in structural systems utilizing artificial neural networks and proper orthogonal decomposition", Struct. Control Health Monitor., 26(2), https://doi.org/10.1002/stc.2288.
  9. Eberhart, R. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the Sixth International Symposium, Nagoya, Japan, 4-6 October.
  10. Friswell, M., Penny, J. and Garvey, J. (1998), "A combined genetic and eigensensitivity algorithm for the location of damage in structures", Comput. Struct., 69(5), 547-556. https://doi.org/10.1016/S0045-7949(98)00125-4
  11. Fatahi, L. and Moradi, S. (2018), "Multiple crack identification in frame structures using a hybrid Bayesian model class selection and swarm-based optimization methods", Struct. Health Monitor., 17(1), 39-58. https://doi.org/10.1177/1475921716683360
  12. Fallah, N., Vaez, SRH. and Mohammadzadeh, A. (2018), "Multidamage identification of large-scale truss structures using a twostep approach", J. Build Eng., https://doi.org/10.1016/j.jobe.2018.06.007.
  13. Figueiredo, E., Park, G., Figueiras, J., Farrar, C. and Worden, K. (2009), "Structural health monitoring algorithm comparisons using standard data sets", Report No. LA-14393; Los Alamos National Laboratory, Los Alamos.
  14. Gordan, M., Razak, H.A., Ismail, Z. and Ghaedi, k. (2017), "Recent Developments in Damage Identification of Structures Using Data Mining", Latin American J. Solid Struct., 14(13), 2373-2401. https://doi.org/10.1590/1679-78254378
  15. Gomes, G.F., Mendez, Y.A.D., Alexandrino P.D.S.L., Da Cunha, S.S. and Ancelotti, A.C. (2018), "A review of vibration based inverse methods for damage detection and identification in mechanical structures using optimization algorithms and ANN", Arch. Comput. Method Eng., 1-15. https://doi.org/10.1007/s11831-018-9273-4.
  16. Gholizadeh, S., Davoudi, H. and Fattahi, F. (2017), "Design of steel frames by an enhanced moth-flame optimization algorithm", Steel Compos Struct., 24(1), 129-140. https://doi.org/10.12989/scs.2017.24.1.129
  17. Ghannadi, P. and Kourehli, S.S. (2018), "Investigation of the accuracy of different finite element model reduction techniques", Struct. Monitor Maintenance., 5(3), 417-428. https://doi.org/10.12989/SMM.2018.5.3.417
  18. Gillich, G.R., Furdui, H., Wahab, M.A. and Korka, Z.I. (2019), "A robust damage detection method based on multi-modal analysis in variable temperature conditions", Mech. Syst. Signal Process., 115, 361-379. https://doi.org/10.1016/j.ymssp.2018.05.037
  19. Giagopoulos, D., Arailopoulos, A., Dertimanis, V., Papadimitriou, C., Chatzi, E. and Grompanopoulos, K. (2019), "Structural health monitoring and fatigue damage estimation using vibration measurements and finite element model updating", Struct. Health Monitor. https://doi.org/10.1177/1475921718790188
  20. Hao, H. and Xia, Y. (2002), "Vibration-based damage detection of structures by genetic algorithm", J. Comput. Civil Eng., 16(3), 222-229. https://doi.org/10.1061/(ASCE)0887-3801(2002)16:3(222)
  21. Hosseinlou, F., Mojtahedi, A. and Yaghin, MAL. (2017), "Developing a SIM strategy for offshore jacket platforms based on the FE model updating and a novel simplified method", Ocean Eng., 145, 158-176. https://doi.org/10.1016/j.oceaneng.2017.08.013
  22. Khatir, S., Belaidi, I., Serra, R., Benaissa, B. and Saada, A. A. (2015), "Genetic algorithm based objective functions comparative study for damage detection and localization in beam structures", J. Physics: Conference Series. http://doi.org/10.1088/1742-6596/628/1/012035
  23. Khatir, S., Dekemele, K., Loccufier, M., Khatir, T. and Wahab, M. A. (2018), "Crack identification method in beam-like structures using changes in experimentally measured frequencies and Particle Swarm Optimization", Comptes Rendus Mecanique., 346(2), 110-120. https://doi.org/10.1016/j.crme.2017.11.008
  24. Kourehli, S.S., Amiri, G.G., Ghafory-Ashtiany, M. and Bagheri, A. (2013a), "Structural damage detection based on incomplete modal data using pattern search algorithm", J. Vib. Control., 19(6), 821-833. https://doi.org/10.1177/1077546312438428
  25. Kourehli, S.S., Bagheri, A., Amiri, G.G. and Ashtiany, M.G. (2013b), "Structural damage detection using incomplete modal data and incomplete static response", KSCE J. Civil Eng., 17(1), 216-223. https://doi.org/10.1007/s12205-012-1864-2
  26. Kaveh, A. and Talatahari, S. (2010), "A novel heuristic optimization method: charged system search", Acta Mechanica., 213(3-4), 267-289. https://doi.org/10.1007/s00707-009-0270-4
  27. 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. Software., 80, 93-100. https://doi.org/10.1016/j.advengsoft.2014.09.010
  28. Kaveh, A., Dadras, A. (2017), "A novel meta-heuristic optimization algorithm: thermal exchange optimization", Adv. Eng. Software., 110, 69-84. https://doi.org/10.1016/j.advengsoft.2017.03.014
  29. Kaveh, A. and Dadras, A. (2018), "Structural damage identification using an enhanced thermal exchange optimization algorithm", Eng. Opt., 50(3), 430-451. https://doi.org/10.1080/0305215X.2017.1318872
  30. Mares, C. and Surace, C. (1996), "An application of genetic algorithms to identify damage in elastic structures", J. Sound Vib., 195(2), 195-215. https://doi.org/10.1006/jsvi.1996.0416
  31. Moezi, S.A., Zakeri, E. and Zare, A. (2018), "Structural single and multiple crack detection in cantilever beams using a hybrid Cuckoo-Nelder-Mead optimization method", Mech. Syst. Signal Process., 99, 805-831. https://doi.org/10.1016/j.ymssp.2017.07.013
  32. Mirjalili, S. (2015), "Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm", Knowledge-Based Syst., 89, 228-249. https://doi.org/10.1016/j.knosys.2015.07.006
  33. Mohanty, B. (2018), "Performance analysis of moth flame optimization algorithm for AGC system", J. Model. Simul., 1-15. https://doi.org/10.1080/02286203.2018.1476799
  34. MATLAB (2018), MATLAB Documentation.; MathWorks, Massachusetts, USA. https://www.mathworks.com/help/matlab
  35. Perera, R. and Torres, R. (2006), "Structural damage detection via modal data with genetic algorithms", J. Struct. Eng., 132(9), 1491-1501. https://doi.org/10.1061/(ASCE)0733-9445(2006)132:9(1491)
  36. Perera, R., Ruiz, A. and Manzano, C. (2009), "Performance assessment of multicriteria damage identification genetic algorithms", Comput. Struct., 87(1-2), 120-127. https://doi.org/10.1016/j.compstruc.2008.07.003
  37. Ruotolo, R. and Surace, C. (1997), "Damage assessment of multiple cracked beams: numerical results and experimental validation", J. Sound Vib., 206(4), 567-588. https://doi.org/10.1006/jsvi.1997.1109
  38. Rasouli, A., Amiri, G.G., Kheyroddin, A., Ashtiany, G.M. and Kourehli, S.S (2014), "A new method for damage prognosis based on incomplete modal data via an evolutionary algorithm", Europe. J. Environ. Civil Eng., 18(3), 253-270. https://doi.org/10.1080/19648189.2014.881758
  39. Rao, R. (2016), "Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems", J. Industrial Eng. Comput., 7(1), 19-34.
  40. Rasouli, A., Kourehli, S.S., Amiri, G.G. and Kheyroddin, A. (2015), "A two-stage method for structural damage prognosis in shear frames based on story displacement index and modal residual force", Adv. Civil Eng. http://dx.doi.org/10.1155/2015/527537
  41. Rageh, A., Linzell, D. G. and Azam, S. E. (2018), "Automated, strain-based, output-only bridge damage detection", J. Civil Struct. Health Monitor., 8(5), 833-846. https://doi.org/10.1007/s13349-018-0311-6
  42. Seyedpoor, S. (2012), "A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization", J. Non-Linear Mech., 47(1), 1-8. https://doi.org/10.1016/j.ijnonlinmec.2011.07.011
  43. Seyedpoor, S.M., Montazer, M. (2016), "A two-stage damage detection method for truss structures using a modal residual vector based indicator and differential evolution algorithm", Smart Struct. Syst., 17(2), 347-361. https://doi.org/10.12989/sss.2016.17.2.347
  44. Shabbir, F., Khan, M.I., Ahmad. N., Tahir, M.F., Ejaz, N. and Hussain, J. (2017), "Structural Damage Detection with Different Objective Functions in Noisy Conditions Using an Evolutionary Algorithm", Appl. Sci., 7(12), 1-26.
  45. Shokrani, Y., Dertimanis, V. K., Chatzi, E. N. and N. Savoia, M. (2018), "On the use of mode shape curvatures for damage localization under varying environmental conditions", Struct. Control Health Monitor., 25(4), https://doi.org/10.1002/stc.2132.
  46. Tiachacht, S., Bouazzouni, A., Khatir, S., Abdel Wahab, M., Behtani, A. and Capozucca, R. (2018), "Damage assessment in structures using combination of a modified Cornwell indicator and genetic algorithm", Eng. Struct., 177, 421-430. https://doi.org/10.1016/j.engstruct.2018.09.070
  47. Tran-Ngoc, H., Khatir, S., De Roeck, G., Bui-Tien, T., Nguyen-Ngoc, L. and Abdel Wahab, M. (2018), "Model Updating for Nam O Bridge Using Particle Swarm Optimization Algorithm and Genetic Algorithm". Sensors., 18(12), 4131. https://doi.org/10.3390/s18124131
  48. Vakil Baghmisheh, M.T., Peimani, M., Sadeghi, M.H. and Ettefagh, M.M. (2008), "Crack detection in beam-like structures using genetic algorithms", Appl. Soft Comput., 8(2), 1150-1160. https://doi.org/10.1016/j.asoc.2007.10.003
  49. Vaez, S.R.H. and Fallah, N. (2017), "Damage detection of thin plates using GA-PSO algorithm based on modal data", Arabian J. Sci. Eng., 42(3), 1251-1263. https://doi.org/10.1007/s13369-016-2398-6
  50. Vakil Baghmisheh, M.T., Peimani, M., Sadeghi, M.H. and Tabrizi, A.F. (2012), "A hybrid particle swarm-Nelder-Mead optimization method for crack detection in cantilever beams", Appl. Soft Comput., 12(8), 2217-2226. https://doi.org/10.1016/j.asoc.2012.03.030
  51. Wei, Z., Liu, J. and Lu, Z. (2018), "Structural damage detection using improved particle swarm optimization", Inverse Problems Sci. Eng., 26(6), 792-810. https://doi.org/10.1080/17415977.2017.1347168
  52. Zhou, Y. L., Maia, N. M., Sampaio, R. P. and Abdel Wahab, M. (2017), "Structural damage detection using transmissibility together with hierarchical clustering analysis and similarity measure", Struct. Health Monitor., 16(6), 711-731. https://doi.org/10.1177/1475921716680849
  53. Zhou, Y. L., Maia, N. M. and Abdel Wahab, M. (2018), "Damage detection using transmissibility compressed by principal component analysis enhanced with distance measure", J. Vib. Control., 24(10), 2001-2019. https://doi.org/10.1177/1077546316674544

Cited by

  1. Efficiency of grey wolf optimization algorithm for damage detection of skeletal structures via expanded mode shapes vol.23, pp.13, 2019, https://doi.org/10.1177/1369433220921000
  2. An effective method for damage assessment based on limited measured locations in skeletal structures vol.24, pp.1, 2019, https://doi.org/10.1177/1369433220947193
  3. A System Identification-Based Damage-Detection Method for Gravity Dams vol.2021, 2021, https://doi.org/10.1155/2021/6653254
  4. Damage detection in structures using Particle Swarm Optimization combined with Artificial Neural Network vol.28, pp.1, 2021, https://doi.org/10.12989/sss.2021.28.1.001