Structural Monitoring and Maintenance

  • 제10권1호
  • /
  • Pages.63-86
  • /
  • 2023
  • /
  • 2288-6605(pISSN)
  • /
  • 2288-6613(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Damage detection technique in existing structures using vibration-based model updating

  • Devesh K. Jaiswal (School of Infrastructure, Indian Institute of Technology Bhubaneswar) ;
  • Goutam Mondal (School of Infrastructure, Indian Institute of Technology Bhubaneswar) ;
  • Suresh R. Dash (School of Infrastructure, Indian Institute of Technology Bhubaneswar) ;
  • Mayank Mishra (School of Infrastructure, Indian Institute of Technology Bhubaneswar)
  • 투고 : 2021.09.10
  • 심사 : 2023.03.17
  • 발행 : 2023.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

Structural health monitoring and damage detection are essential for assessing, maintaining, and rehabilitating structures. Most of the existing damage detection approaches compare the current state structural response with the undamaged vibrational structural response, which is unsuitable for old and existing structures where undamaged vibrational responses are absent. One of the approaches for existing structures, numerical model updating/inverse modelling, available in the literature, is limited to numerical studies with high-end software. In this study, an attempt is made to study the effectiveness of the model updating technique, simplify modelling complexity, and economize its usability. The optimization-based detection problem is addressed by using programmable open-sourced code, OpenSees® and a derivative-free optimization code, NOMAD®. Modal analysis is used for damage identification of beam-like structures with several damage scenarios. The performance of the proposed methodology is validated both numerically and experimentally. The proposed method performs satisfactorily in identifying both locations and intensity of damage in structures.

키워드

과제정보

This work is supported by the Ministry of Human Resource Development, Government of India.

참고문헌

  1. Arefi S.L. and Gholizad A. (2020), "Damage identification of structures by reduction of dynamic matrices using the modified modal strain energy method", Struct. Monit. Maint., 7(2), 125-147. https://doi.org/10.12989/smm.2020.7.2.125.
  2. Audet, C. and Dennis Jr, J.E. (2006), "Mesh adaptive direct search algorithms for constrained optimization", Soc. Ind. Appl. Math., 17(1), 188-217. https://doi.org/10.1137/040603371.
  3. Audet, C. and Hare, W. (2017), Derivative-Free and Blackbox Optimization, Springer Series in Operations Research and Financial Engineering, Springer International Publishing, Switzerland. https://doi.org/10.1007/978-3-319-68913-5.
  4. Azim, M.R., Zhang, H. and Mustafa, G. (2020), "Damage detection of railway bridges using operational vibration data: theory and experimental verifications", Struct. Monit. Maint., 7(2), 149-166. https://doi.org/10.12989/smm.2020.7.2.149.
  5. Bahrami, S., Tribes, C., Devals, C., Vu, T.C. and Guibault, F. (2016), "Multi-fidelity shape optimization of hydraulic turbine runner blades using a multi-objective mesh adaptive direct search algorithm", Appl. Math. Model., 40, 1650-1668. https://doi.org/10.1016/j.apm.2015.09.008.
  6. Barman, S.K., Maiti, D.K. and Maity, D. (2020), "Damage detection of truss employing swarm-based optimization techniques : A comparison", Advanced Engineering Optimization Through Intelligent Techniques, 949, 21-37. https://doi.org/10.1007/978-981-13-8196-6_3.
  7. Beck (2010), "Bayesian system identification based on probability logic", Struct. Control Health Monitoring, 17, 825-847. https://doi.org/10.1002/stc.424.
  8. Behmanesh, I. and Moaveni, B. (2015), "Probabilistic identification of simulated damage on the Dowling Hall footbridge through Bayesian finite element model updating", Struct. Control Health Monit., 22(3), 463-483. https://doi.org/10.1002/stc.1684.
  9. Behmanesh, I., Moaveni, B., Lombaert, G. and Papadimitriou, C. (2015), "Hierarchical Bayesian model updating for structural identification", Mech. Syst. Signal Pr., 64, 360-376. https://doi.org/10.1016/j.ymssp.2015.03.026.
  10. Ching, J., Beck, J.L. and Porter, K.A. (2006), "Bayesian state and parameter estimation of uncertain dynamical systems", Probabilist. Eng. Mech., 21(1), 81-96. https://doi.org/10.1016/j.probengmech.2005.08.003.
  11. Dinh-cong, D., Nguyen-thoi, T. and Nguyen, D.T. (2020), "A FE model updating technique based on SAP2000-OAPI and enhanced SOS algorithm for damage assessment of full-scale structures", Appl. Soft Comput. J., 89, 106100. https://doi.org/10.1016/j.asoc.2020.106100.
  12. Dube, O., Dube, D., Chaouki, J. and Bertrand, F. (2014), "Optimization of detector positioning in the radioactive particle tracking technique", Appl. Radiation Isotopes, 89, 109-124. https://doi.org/10.1016/j.apradiso.2014.02.019.
  13. Erazo, K., Moaveni, B. and Nagarajaiah, S. (2019), "Bayesian seismic strong-motion response and damage estimation with application to a full-scale seven story shear wall structure", Eng. Struct., 186, 146-160. https://doi.org/10.1016/j.engstruct.2019.02.017.
  14. Erazo, K. and Nagarajaiah, S. (2017), "An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering", J. Sound Vib., 397, 222-240. https://doi.org/10.1016/j.jsv.2017.03.001.
  15. Farrar, C., Doebling, S. and Nix, D. (2001), "Vibration-based structural damage identification", Philos. T. R. Soc. A, 359, 131-149. https://doi.org/10.1098/rsta.2000.0717.
  16. Fowler, K.R., Reese, J.P., Kees, C.E., Dennis Jr, J.E., Kelley, C.T., Miller, C.T., Audet, C., Booker, A.J., Couture, G., Darwin, R.W., Farthing, M.W., Finkel, D.E., Gablonsky, J.M., Gray, G., and Kolda, T.G. (2008), "Comparison of derivative-free optimization methods for groundwater supply and hydraulic capture community problems", Adv. Water Resour., 31(5), 743-757. https://doi.org/10.1016/j.advwatres.2008.01.010.
  17. Inman, D., Farrar, C. and Lopes, V. (2005), Damage Prognosis: For Aerospace, Civil and Mechanical Systems, Wiley.
  18. Jafarkhani, R. and Masri, S.F. (2011), "Finite Element Model Updating Using Evolutionary Strategy for Damage Detection", Comput. - Aided Civil Infrastruct. Eng., 26(3), 207-224. https://doi.org/10.1111/j.1467-8667.2010.00687.x.
  19. Jaiswal, D.K., Dash, S.R. and Mondal, G. (2020), "Development of an effective and efficient baseline free damage detection scheme for structural health monitoring", Proceedings of the Indian Structural Steel Conference, Hyderabad, India, March.
  20. Jin, S. and Jung, H. (2016), "Sequential surrogate modeling for efficient finite element model updating", Comput. Struct. J., 168, 30-45. https://doi.org/10.1016/j.compstruc.2016.02.005.
  21. Jin, S.S., Cho, S., Jung, H.J., Lee, J.J. and Yun, C.B. (2014), "A new multi-objective approach to finite element model updating", J. Sound Vib., 333(11), 2323-2338. https://doi.org/10.1016/j.jsv.2014.01.015.
  22. Kaveh, A. and Zolghadr, A. (2017), "Guided modal strain energy-based approach for structural damage identification using tug-of-war optimization algorithm", J. Comput. Civil Eng., 31(4), 04017016. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000665.
  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. Khatir, S., Wahab, M.A., Boutchicha, D. and Khatir, T., (2019), "Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis", J. Sound Vib., 448, 230-246. https://doi.org/10.1016/j.jsv.2019.02.017.
  25. Le Digabel, S. (2011), "Algorithm 909: NOMAD: Nonlinear optimization with the MADS algorithm", ACM T. Math. Software, 37(4), 1-15. https://doi.org/10.1145/1916461.1916468.
  26. Majumdar, A., Nanda, B., Maiti, D.K. and Maity, D. (2014), "Structural damage detection based on modal parameters using continuous ant colony optimization", Adv. Civil Eng., 2014, 1-14. https://doi.org/10.1155/2014/174185.
  27. McKenna, F. (2011), "OpenSees: a framework for earthquake engineering simulation", Comput. Sci. Eng., 13(4), 58-66. https://doi.org/10.1109/MCSE.2011.66.
  28. Meruane, V. and Heylen, W. (2011), "An hybrid real genetic algorithm to detect structural damage using modal properties", Mech. Syst. Signal Pr., 25(5), 1559-1573. https://doi.org/10.1016/j.ymssp.2010.11.020.
  29. Mirjalili, S. (2015), "The ant lion optimiser", Adv. Eng. Softw., 83, 80-98. https://doi.org/10.1016/j.advengsoft.2015.01.010.
  30. Mishra, M., Barman, S.K., Maity, D. and Maiti, D.K. (2019), "Ant lion optimization algorithm for structural damage detection using vibration data", J. Civil Struct. Health Monit., 9(1), 117-136. https://doi.org/10.1007/s13349-018-0318-z.
  31. Mishra, M., Barman, S.K., Maity, D. and Maiti, D.K. (2020), "Performance studies of 10 metaheuristic techniques in determination of damages for large-scale spatial trusses from changes in vibration responses", J. Comput. Civil Eng., 34(2), 04019052. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000872.
  32. Moaveni, B., He, X., Conte, J.P. and De Callafon, R.A. (2008), "Damage identification of a composite beam using finite element model updating", Comput. - Aided Civil Infrastruct. Eng., 23(5), 339-359. https://doi.org/10.1111/j.1467-8667.2008.00542.x.
  33. Moaveni, B., He, X., Conte, J.P. and Restrepo, J.I. (2010), "Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table", Struct. Saf., 32(5), 347-356. https://doi.org/10.1016/j.strusafe.2010.03.006.
  34. Moaveni, B., Hurlebaus, S. and Moon, F. (2013), "Special issue on real-world applications of structural identification and health monitoring methodologies", J. Struct. Eng. - ASCE, 139(10), 1637-1638. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000779.
  35. Mohan, S.C., Maiti, D.K. and Maity, D. (2013), "Structural damage assessment using FRF employing particle swarm optimization", Appl. Math. Comput., 219(20), 10387-10400. https://doi.org/10.1016/j.amc.2013.04.016.
  36. Nagarajaiah, S. and Erazo, K. (2016), "Structural monitoring and identification of civil infrastructure in the United States", Struct. Monit. Maint., 3(1), 51-69. http://dx.doi.org/10.12989/smm.2016.3.1.051.
  37. Nguyen, C., Huynh, T.C. and Kim, T. (2018), "Vibration-based damage detection in wind turbine towers using artificial neural networks", Struct. Monit. Maint., 5(4), 507-519. https://doi.org/10.12989/smm.2018.5.4.507.
  38. Pastor, M., Binda, M. and Harcarik, T. (2012), "Modal assurance criterion", Procedia Eng., 48, 543-548. https://doi.org/10.1016/j.proeng.2012.09.551.
  39. Qiao, P. and Fan, W. (2014), "Lamb wave-based damage imaging method for damage detection of rectangular composite plates", Struct. Monit. Maint., 1(4), 411-425. http://dx.doi.org/10.12989/smm.2014.1.4.411.
  40. Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2011), "Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems", Comput. Aided Design, 43(3), 303-315. https://doi.org/10.1016/j.cad.2010.12.015.
  41. Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2012), "Teaching-learning based optimization: An optimization method for continuous nonlinear large scale problems", Inform. Sci., 183 (1), 1-15. https://doi.org/10.1016/j.ins.2011.08.006.
  42. Razavi, M. and Hadidi, A. (2020), "Assessment of sensitivity-based FE model updating technique for damage detection in large space structures", Struct. Monit. Maint., 7(3), 261-281. https://doi.org/10.12989/smm.2020.7.3.261.
  43. Rios, L. And Sahinidis, N. (2010), "Derivative-free optimization: A review of algorithms and comparison of software implementations", J. Global Optim., 56(3), 1247-1293. https://doi.org/10.1007/s10898-012-9951-y.
  44. Schallhorn, C. and Rahmatalla, S. (2015), "Crack detection and health monitoring of highway steel-girder bridges", Struct. Health Monit., 14(3), 281-299. https://doi.org/10.1177/1475921714568404.
  45. Smyl, D., Pour-Ghaz, M. and Seppanen, A. (2018), "Detection and reconstruction of complex structural cracking patterns with electrical imaging", NDT & E Int., 99, 123-133. https://doi.org/10.1016/j.ndteint.2018.06.004.
  46. Som, S., Maity, S., Som, B. and Sur, S. (2019), Dominant Failure Path Prediction Of Majherhat Bridge Collapse At Kolkata, Indian Highways, June, 47(6), 20-29.
  47. Stubbs, N. and Kim, J.T. (1996), "Damage localization in structures without baseline modal parameters", AIAA J., 34(8), 1644-1649. https://doi.org/10.2514/3.13284.
  48. Sun, H., and Buyukozturk, O. (2016), "Bayesian model updating using incomplete modal data without mode matching", Proceedings of SPIE, 9805, 108-116. https://doi.org/10.1117/12.2219300.
  49. Varma, T.V., Sarkar, S. and Mondal, G. (2020), "Buckling restrained sizing and shape optimization of truss structures", J. Struct. Eng., 146(5), 04020048. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002590.
  50. Wu, M. and Smyth, A.W. (2007), "Application of the unscented Kalman filter for real-time nonlinear structural system identification", Struct. Control Health Monit., 14(7), 971-990. https://doi.org/10.1002/stc.186.
  51. Zanardo, G., Hao, H., Xia, Y. and Deeks, A.J. (2006), "Stiffness assessment through modal analysis of an RC slab bridge before and after strengthening", J. Bridge Eng., 11(5), 590-601. https://doi.org/10.1061/(ASCE)1084-0702(2006)11:5(590).