Journal of Civil Structural Health Monitoring

, Volume 9, Issue 5, pp 741–755 | Cite as

Vibration-based structural health monitoring using symbiotic organism search based on an improved objective function

  • Milad Jahangiri
  • Mohammad Ali HadianfardEmail author
Original Paper


Vibration-based structural health monitoring (VSHM) relying on model updating methods has been developed greatly and nowadays, not only serves as a major subset of SHM, but also shapes a special class of optimization problems. The historical course of evolution of this field via different research groups and with different goals and objectives, has resulted in the emergence of multiple objective functions, each appropriate only for certain damage scenarios and incapable of reasonably addressing others. The natural frequency residual (NFR) is an objective function sensitive to the damage intensity, which in the meantime, fails to predict the damage location in the symmetric structures. The total modal assurance criterion (TMAC) is another objective function which is sensitive to the damage position, but fails to estimate of the damage severity in the uniformly damaged structures. The present work successfully provides an innovative solution to unify both aforementioned objectives in a holistic objective function (HOF), through a particular combination of NFR and TMAC. Additionally, the competency of the above HOF for solving the VSHM problems has been investigated and demonstrated using a symbiotic organism search (SOS) optimization algorithm. The robustness and efficiency of the proposed VSHM method are verified through assessment of two un-damped benchmark structures. The obtained results indicate that in all damage scenarios, the HOF predicts with a high precision the damage location and succeeds in the high accuracy estimation of the damage extent. Consequently, the combination of the proposed HOF criterion and the SOS optimization algorithm is recommended as a reliable technique for VSHM.


Structural health monitoring Damage localization Damage quantification Holistic objective function Symbiotic organism search 



The authors wish to thank Dr. Mazdak Hashempour from Politecnico di Milano for reviewing the manuscript and his precious comments. Also the authors would like to thank Dr. Mehdi Jahangiri from Shiraz University for his technical involvement in this research work.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Ding Z, Yao R, Huang J, Huang M, Lu Z (2017) Structural damage detection based on residual force vector and imperialist competitive algorithm. Struct Eng Mech 62(6):709–717Google Scholar
  2. 2.
    Pnevmatikos NG, Hatzigeorgiou GD (2017) Damage detection of framed structures subjected to earthquake excitation using discrete wavelet analysis. Bull Earthq Eng 15(1):227–248CrossRefGoogle Scholar
  3. 3.
    Esfandiari A, Sanayei M, Bakhtiari-Nejad F, Rahai A (2010) Finite element model updating using frequency response function of incomplete strain data. AIAA J 48(7):1420–1433CrossRefGoogle Scholar
  4. 4.
    Fallahian S, Joghataie A, Kazemi M (2018) Damage identification in structures using time domain response based on differential evolutionary algorithm. Int J Optim Civil Eng 8(3):357–380Google Scholar
  5. 5.
    Jayawardhana M, Zhu X, Liyanapathirana R, Gunawardana U (2017) Compressive sensing for efficient health monitoring and effective damage detection of structures. Mech Syst Signal Process 84:414–430CrossRefGoogle Scholar
  6. 6.
    Doebling SW, Farrar CR, Prime MB, Shevitz DW (1996) Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review (No. LA-13070-MS). Los Alamos National Lab, New MexicoCrossRefGoogle Scholar
  7. 7.
    Hadianfard MA, Rabieea R, Sarshadb A (2015) Case study on the effects of retrofitting on changing structural dynamic characteristics by microtremor measurements and finite element analysis. Struct Eng Mech 55(5):965–977CrossRefGoogle Scholar
  8. 8.
    Hicks SJ (2004) Comparative structure cost of modern commercial buildings. Steel Construction InstituteGoogle Scholar
  9. 9.
    Hadianfard MA, Rabiee R, Sarshad A (2017) Assessment of vulnerability and dynamic characteristics of a historical building using microtremor measurements. Int J Civil Eng 15(2):175–183CrossRefGoogle Scholar
  10. 10.
    Khoshnoudian F, Esfandiari A (2011) Structural damage diagnosis using modal data. Scientia Iranica 18(4):853–860CrossRefGoogle Scholar
  11. 11.
    Holland JH (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press, CambridgeCrossRefGoogle Scholar
  12. 12.
    Shi Z, Law S, Zhang L (2000) Damage localization by directly using incomplete mode shapes. J Eng Mech 126(6):656–660CrossRefGoogle Scholar
  13. 13.
    Majumdar A, Maiti DK, Maity D (2012) Damage assessment of truss structures from changes in natural frequencies using ant colony optimization. Appl Math Comput 218(19):9759–9772zbMATHGoogle Scholar
  14. 14.
    Perera R, Torres R (2006) Structural damage detection via modal data with genetic algorithms. J Struct Eng 132(9):1491–1501CrossRefGoogle Scholar
  15. 15.
    Perera R, Marin R, Ruiz A (2013) Static–dynamic multi-scale structural damage identification in a multi-objective framework. J Sound Vib 332(6):1484–1500CrossRefGoogle Scholar
  16. 16.
    Sun R, Perera R, Sevillano E, Gu J (2018) Parameter identification of composite materials based on spectral model by using model updating method. Int J Polym Sci 2018:7310846Google Scholar
  17. 17.
    Shabbir F, Khan MI, Ahmad N, Tahir MF, Ejaz N, Hussain J (2017) Structural damage detection with different objective functions in noisy conditions using an evolutionary algorithm. Appl Sci 7(12):1245CrossRefGoogle Scholar
  18. 18.
    Allemang RJ, Brown DL (1982) A correlation coefficient for modal vector analysis. In: Proceedings of the 1st international modal analysis conference, SEM Orlando, pp 110–116Google Scholar
  19. 19.
    Ewins D (2003) Modal testing: theory, practice and application (mechanical engineering research studies: engineering dynamics series). Research studies Pre, 2nd edn. ISBN-13: 978-0863802188Google Scholar
  20. 20.
    Gao Y, Spencer B (2002) Damage localization under ambient vibration using changes in flexibility. Earthq Eng Eng Vib 1(1):136–144CrossRefGoogle Scholar
  21. 21.
    Görl E, Link M (2003) Damage identification using changes of eigenfrequencies and mode shapes. Mech Syst Signal Process 17(1):103–110CrossRefGoogle Scholar
  22. 22.
    Alkayem NF, Cao M, Zhang Y, Bayat M, Su Z (2018) Structural damage detection using finite element model updating with evolutionary algorithms: a survey. Neural Comput Appl 30(2):389–411CrossRefGoogle Scholar
  23. 23.
    Georgioudakis M, Plevris V (2018) A combined modal correlation criterion for structural damage identification with noisy modal data. Adv Civil Eng 2018:3183067CrossRefGoogle Scholar
  24. 24.
    Shih HW, Thambiratnam DP, Chan TH (2011) Damage detection in truss bridges using vibration based multi-criteria approach. Struct Eng Mech 39(2):187CrossRefGoogle Scholar
  25. 25.
    Shih HW, Thambiratnam DP, Chan TH (2009) Vibration based structural damage detection in flexural members using multi-criteria approach. J Sound Vib 323(3–5):645–661CrossRefGoogle Scholar
  26. 26.
    Shih HW, Thambiratnam DP, Chan THT (2013) Damage detection in slab-on-girder bridges using vibration characteristics. Struct Control Health Monit 20(10):1271–1290CrossRefGoogle Scholar
  27. 27.
    Jahangiri M, Ahmadi B, Rahimi H (2015) Application of single-objective optimization techniques for structural health monitoring. In: 2nd International & 6th National Conference on Earthquake & Structures, At ACECR of Kerman, Kerman, IranGoogle Scholar
  28. 28.
    Jahangiri M, Ahmadi B, Rahimi H (2015) Structural damage localization and quantification based on multi-objective optimization method. In: 2nd International & 6th National Conference on Earthquake & Structures, At ACECR of Kerman, Kerman, IranGoogle Scholar
  29. 29.
    Jahangiri M, Ahmadi-Nedushan B (2016) Structural damage identification using MOPSO and MOEA/D multi-objective evolutionary optimization algorithms. J Ferdowsi Civil Eng 30(1):63–77Google Scholar
  30. 30.
    Jahangiri M, Hadianfard MA, Najafgholipour MA (2019) Comparison of single and multi-objective particle swarm optimization algorithm in order to structural health monitoring. In: 3nd International & 6th National Conference on Applied Researches in Structural Engineering and Construction Management, Tehran, IranGoogle Scholar
  31. 31.
    Seyedpoor S (2012) A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization. Int J Non-Linear Mech 47(1):1–8MathSciNetCrossRefGoogle Scholar
  32. 32.
    Voß S, Martello S, Osman IH, Roucairol C (eds) (2012) Meta-heuristics: advances and trends in local search paradigms for optimization. Springer, Boston, MAGoogle Scholar
  33. 33.
    Birattari M, Paquete L, Strutzle T, Varrentrapp K (2001) Classification of metaheuristics and design of experiments for the analysis of components. Technical Report. AIDA-01-05Google Scholar
  34. 34.
    Cheng M-Y, Prayogo D (2014) Symbiotic organisms search: a new metaheuristic optimization algorithm. Comput Struct 139:98–112CrossRefGoogle Scholar
  35. 35.
    Ezugwu AE, Prayogo D (2018) Symbiotic organisms search algorithm: theory, recent advances and applications. Expert Syst Appl 119:184–209CrossRefGoogle Scholar
  36. 36.
    Tejani GG, Savsani VJ, Bureerat S, Patel VK (2017) Topology and size optimization of trusses with static and dynamic bounds by modified symbiotic organisms search. J Comput Civil Eng 32(2):04017085CrossRefGoogle Scholar
  37. 37.
    Tejani GG, Savsani VJ, Patel VK, Mirjalili S (2018) Truss optimization with natural frequency bounds using improved symbiotic organisms search. Knowl-Based Syst 143:162–178CrossRefGoogle Scholar
  38. 38.
    Tejani GG, Savsani VJ, Patel VK (2016) Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization. J Comput Des Eng 3(3):226–249Google Scholar
  39. 39.
    Humar J (2012) Dynamics of structures. CRC Press, FloridazbMATHGoogle Scholar
  40. 40.
    Chopra AK (2017) Dynamics of structures. Theory and applications to earthquake engineering. CRC PressGoogle Scholar
  41. 41.
    Ogata K, Yang Y (2002) Modern control engineering, vol 4. Prentice hall India, New JerseyGoogle Scholar
  42. 42.
    Wickramasinghe WR, Thambiratnam DP, Chan TH, Nguyen T (2016) Vibration characteristics and damage detection in a suspension bridge. J Sound Vib 375:254–274CrossRefGoogle Scholar
  43. 43.
    Fang SE, Perera R, De Roeck G (2008) Damage identification of a reinforced concrete frame by finite element model updating using damage parameterization. J Sound Vib 313:544–559CrossRefGoogle Scholar
  44. 44.
    Sapp J (1994) Evolution by association: a history of symbiosis. Oxford University Press on Demand, OxfordGoogle Scholar
  45. 45.
    Hyndman RJ, Koehler AB (2006) Another look at measures of forecast accuracy. Int J Forecast 22(4):679–688CrossRefGoogle Scholar
  46. 46.
    Messina A, Williams E, Contursi T (1998) Structural damage detection by a sensitivity and statistical-based method. J Sound Vib 216(5):791–808CrossRefGoogle Scholar
  47. 47.
    Jahangiri M, Najafgholipour MA, Dehghan SM, Hadianfard MA (2019) The efficiency of a novel identification method for structural damage assessment using the first vibration mode data. J Sound Vib 458:1–16CrossRefGoogle Scholar
  48. 48.
    Perera R, Fang SE (2010) Multi-objective damage identification using particle swarm optimization techniques. In: Nedjah N, dos Santos Coelho L, de Macedo Mourelle L (eds) Multi-objective swarm intelligent systems. Springer, Berlin, Heidelberg, pp 179–207CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringShiraz University of TechnologyShirazIran

Personalised recommendations