Structural damage detection using time domain responses and teaching–learning-based optimization (TLBO) algorithm

Document Type : Article


1 Department of Civil Engineering, Sharif Univers ity of Technology, International Campus, Kish Island , Iran

2 Faculty Member, Civil Engineering Department, Sharif University of Technology, Tehran, Iran

3 Dept. of Civil Eng. Sharif University of Eng. Tehran, Iran


Nowadays, structural health monitoring has attracted much attention, due to the construction of important and complex structures and their safety. One branch of structural health monitoring is damage detection, estimating the location and extent of eventual damages in the structural systems. In this study, an efficient method is introduced to determine the location and extent of damage in the frame, beam and truss structures using time domain response and an optimization algorithm. First of all, the structural damage detection problem is formulated as a standard optimization problem. So that, the optimization objective function is defined by using the acceleration of damaged structures and analytical model acceleration. The acceleration is obtained using Newmark method. Damage is simulated by reducing the elasticity modulus of structural members. Then, damage problem converted to an optimization problem are solved by teaching–learning-based optimization (TLBO) algorithm therefore, the exact location and extent of damage in structure can be determined. In order to show the capabilities of the proposed approach for identifying structural damage, four illustrative test examples are considered with considering measurement noise effect. The results clearly show that the proposed method is as a powerful method to detect multiple damage in structures.


Main Subjects

1. Fallahian, S. and Seyedpoor, S.M. A two stage
method for structural damage identi cation using an
adaptive neuro-fazzy inference system and particle
swarm optimization", Asian Journal of Civil Engineering
(Building And Housing), 11(6), pp. 797-810 (2010).
2. Kourehli, S.S., Bagheri, A., Ghodrati Amiri, G., and
Ghafory-Ashtiany, M. Structural damage identi cation
method based on incomplete static response using
an optimization problem", Scientia Iranica, 21(4), pp.
1209-1216 (2013).
3. Bagheri, A., Zare Hosseinzadeh, A., Rizzo, P., and
Ghodrati Amiri, G. Time domain damage localization
and quanti cation in seismically excited structures
using a limited number of sensors", Journal of Vibration
and Control, 23(18), pp. 2942-2961 (2016). DOI:
4. Joglekar, D.M. and Mitra, M. Time domain analysis
of nonlinear frequency mixing in a slender beam for
localizing a breathing crack", Smart Materials and
Structures, 26(2), 025009 (2016). DOI: 10.1088/1361-
5. Seyedpoor, S.M. and Montazer, M. A two-stage
damage detection method for truss structures using a
modal residual vector based indicator and di erential
evolution algorithm", Smart Structures and Systems,
17(2), pp. 347-361 (2016).
6. Shayanfar, M.A., Kaveh, A., Eghlidos, O., and
Mirzaei, B. Damage detection of bridge structures in
time domain via enhanced colliding bodies optimization",
Int. J. Optim. Civil Eng., 6(2), pp. 211-226
7. Pandey, A.K., Biswas, M., and Samman, M.M. Damage
detection from changes in curvature mode shapes",
J. Sound. Vib., 145(2), pp. 321-332 (1991).
8. Sohn, H., Farrar, C., Hunter, N., and Worden, K.,
A Review of Structural Health Monitoring Literature:
1996-2001. Los Alamos National Laboratory report,
(LA-13976-MS) (2004).
9. Carden, E.P. and Fanning, P. Vibration based condition
monitoring: A review", Structural Health Monitoring,
3(4), pp. 355-377 (2004).
10. Maity, D. and Tripathy, R.R. Damage assessment of
structures from changes in natural frequencies using
genetic algorithm", Structural Engineering and Mechanics,
19(1), pp. 21-42 (2005).
11. Pawar, P.M. and Ganguli, R. Matrix crack detection
in thin-walled composite beam using genetic fuzzy
system", Journal of Intelligent Material Systems and
Structures, 16(5), pp. 395-409 (2005).
12. Pawar, P.M., Reddy, K.V., and Ganguli, R. Damage
detection in beams using spatial Fourier analysis and
neural networks", Journal of Intelligent Material Systems
and Structures, 18(4), pp. 347-359 (2007).
13. Elshafey, A.A., Marzouk, H., and Haddara, M.R.
Experimental damage identi cation using modi ed
mode shape di erence", Journal of Marine Science and
Application, 10(2), pp. 150-155 (2011).
14. Lu, X.B., Liu, J.K., and Lu, Z.R. A two-step approach
for crack identi cation in beam", Journal of Sound and
Vibration, 332(2), pp. 282-293 (2013).
15. Dawari, V.B. and Vesmawala, G.R. Modal curvature
and modal
exibility methods for honeycomb damage
identi cation in reinforced concrete beams", Journal
of Procedia Engineering, 51, pp. 119-124 (2013).
16. Choi, S., Park, S., Yoon, S., and Stubbs, N. Nondestructive
damage identi cation using changes in modal
compliance", NDT and E International, 38(7), pp.
529-540 (2005).
3100 S. Fallahian et al./Scientia Iranica, Transactions A: Civil Engineering 25 (2018) 3088{3100
17. Seyedpoor, S.M. A two method for structural damage
detection using a modal strain energy index and
particle swarm optimization", International Journal of
Non-Linear Mechanics, 47(1), pp. 1-8 (2012).
18. Bandara, R.P., Chan, T.H., and Thambiratnam, D.P.
Structural damage detection method using frequency
response functions", Journal of Structural Health Monitoring,
13(4), pp. 418-429 (2014).
19. Zimin, V.D. and Zimmerman, D.C. Structural damage
detection using time domain periodogram analysis",
Journal of Structural Health Monitoring, 8(2), pp.
125-135 (2009).
20. Fu, Y.Z., Lu, Z.R., and Liu, J.K. Damage identi -
cation in plates using nite element model updating
in time domain", Journal of Sound and Vibration,
332(26), pp. 7018-7032 (2013).
21. Chopra, A. Dynamics of structures", Theory and
Applications to Earthquake Engineering, Prentice-Hall,
4th Edn., New Jersey (2012).
22. Nouri Shirazi, M.R., Mollamahmoudi, H., and Seyedpoor,
S.M. Structural damage identi cation using
an adaptive multi-stage optimization method based
on a modi ed particle swarm algorithm", Journal of
Optimization Theory and Applications, 160(3), pp.
1009-1019 (2014).
23. Messina, A., Williams, E.J., and Contursi, T. Structural
damage detection by a sensitivity and staticalbased
Method", Journal of Sound and Vibration,
216(5), pp. 791-808 (1998).
24. Rao, R.V., Savsani, V.J., and Vakharia, D.P.
Teaching-learning-based optimization: A novel
method for constrained mechanical design optimization
problems", Computer-Aided Design, 43(3), pp.
303-315 (2011).
25. Dokeroglu, T. Hybrid teaching-learning-based optimization
algorithm for the quadratic assignment problem",
Computers & Industrial Engineering, 85(C), pp.
86-101 (2015).
26. Huang, J., Gao, L., and Li, X. A teaching-learningbased
cuckoo search for constrained engineering design
problems", Advances in Global Optimization, 95, pp.
375-386 (2015).
27. Ouyang, H-B., Gao, L-Q., Kong, X-Y., Zou, D-X.,
and Li, S. Teaching-learning based optimization with
global crossover for global optimization problems",
Applied Mathematics and Computation, 265, pp. 533-
556 (2015).
28. Rao, R.V. and Kalyankar, V.D. Multi-pass turning
process parameter optimization using teachinglearning-
based optimization algorithm", Scientia Iranica,
20(3), pp. 967-974 (2013).
29. Rao, R.V. and Patel, V. An improved teachinglearning-
based optimization algorithm for solving unconstrained
optimization problems", Scientia Iranica,
20(3), pp. 710-720 (2013).
30. Seyedpoor, S.M., Shahbandeh, S., and Yazdanpanah
O. An ecient method for structural damage detection
using a di erential evolution algorithm-based
optimisation approach", Civil Engineering and Environmental
Systems, 32(3), pp. 230-250 (2015).
31. Nobahari, M. and Seyedpoor, S.M. An ecient
method for structural damage localization based on
the concepts of
exibility matrix and strain energy of
a structure", Structural Engineering and Mechanics,
46(2), pp. 231-244 (2013).