Skip to main content
SpringerLink
Log in

Damage identification of a 2D frame structure using two-stage approach

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

In this article, a two-stage damage identification approach is employed to detect the site and extent of multiple damage cases in a 2D frame structure. In the first stage, Damage locating vector (DLV) method based on a new indicator called EDS (Exponential decreased stress) is applied to localize the damaged elements. Next, the damage extents of suspected elements are quantified using two metaheuristic algorithms, Water evaporation optimization (WEO) and accelerated WEO. Numerical example consists of a 2D frame structure with two types of meshing elements, 35 and 105 frame elements. For every state, two multiple damage cases are tested in noisy condition. To compare performance of the two-stage method with one-stage optimization method, the studied cases are also run using these two metaheuristic algorithms. The results indicate that the two-stage approach is more effective than one-stage because the number of intact element detected as damaged one and computational errors for actual damaged elements in one-stage method are more while the two-stage approach spends a much shorter time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M. Naderi and M. Khonsari, Real-time fatigue life monitoring based on thermodynamic entropy, Structural Health Monitoring, 10 (2) (2011) 189–197.

    Article  Google Scholar 

  2. B. Gunes and O. Gunes, Structural health monitoring and damage assessment Part I: A critical review of approaches and methods, International Journal of Physical Sciences, 8 (34) (2013) 1694–1702.

    Google Scholar 

  3. M. Markou and S. Singh, Novelty detection: A review—part 2: Neural network based approaches, Signal Processing, 83 (12) (2003) 2499–2521.

    Article  MATH  Google Scholar 

  4. X. Chen and L. Yu, Flexibility-based objective functions for constrained optimization problems on structural damage detection, Proc. of International Conference on Computeraided Material and Engineering, Hangzhou, China (2011).

    Google Scholar 

  5. M. Nobahari and S. M. Seyedpoor, An efficient method for structural damage localization based on the concepts of flexibility matrix and strain energy of a structure, Structural Engineering and Mechanics, 46 (2) (2013) 231–244.

    Article  Google Scholar 

  6. D. Bernal, Load vectors for damage localization, Journal of Engineering Mechanics, 128 (1) (2002) 7–14.

    Article  Google Scholar 

  7. Y. Gao, B. F. Spencer Jr. and D. Bernal, Experimental verification of the flexibility-based damage locating vector method, Journal of Engineering Mechanics, 133 (10) (2007) 1043–1049.

    Article  Google Scholar 

  8. S. Quek, V. Tran, X. Hou and W. Duan, Structural damage detection using enhanced damage locating vector method with limited wireless sensors, Journal of Sound and Vibration, 328 (4) (2009) 411–427.

    Article  Google Scholar 

  9. T. Vo-Duy, N. Nguyen-Minh, H. Dang-Trung, A. Tran-Viet and T. Nguyen-Thoi, Damage assessment of laminated composite beam structures using Damage locating vector (DLV) method, Frontiers of Structural and Civil Engineering, 9 (4) (2015) 457–465.

    Article  Google Scholar 

  10. D. Dinh-Cong, T. Vo-Duy, N. Nguyen-Minh, V. Ho-Huu and T. Nguyen-Thoi, A two-stage assessment method using damage locating vector method and differential evolution algorithm for damage identification of cross-ply laminated composite beams, Advances in Structural Engineering, 20 (12) (2017) 1807–1827.

    Article  Google Scholar 

  11. T. Nguyen-Thoi, A. Tran-Viet, N. Nguyen-Minh, T. Vo-Duy and V. Ho-Huu, A combination of Damage locating vector method (DLV) and Differential evolution algorithm (DE) for structural damage assessment, Frontiers of Structural and Civil Engineering (2016) 1–17.

    Google Scholar 

  12. S. R. Hoseini Vaez and T. Arefzade, Vibration-based damage detection of concrete gravity dam monolith via wavelet transform, Journal of Vibroengineering, 19 (1) (2017).

    Google Scholar 

  13. S. R. Hoseini Vaez and N. Fallah, Damage detection of thin plates using GA-PSO algorithm based on modal data, Arabian Journal for Science and Engineering, 42 (3) (2017) 1251–1263.

    Article  Google Scholar 

  14. A. Kaveh, S. R. Hoseini Vaez, P. Hosseini and N. Fallah, Detection of damage in truss structures using Simplified Dolphin Echolocation algorithm based on modal data, Smart Structures and Systems, 18 (5) (2016) 983–1004.

    Article  Google Scholar 

  15. J. Xiang, U. Nackenhorst, Y. Wang, Y. Jiang, H. Gao and Y. He, A new method to detect cracks in plate-like structures with though-thickness cracks, Smart Structures and Systems, 14 (3) (2014) 397–418.

    Article  Google Scholar 

  16. S. J. Kim, Damage detection in composite under in-plane load using tap test, Journal of Mechanical Science and Technology, 29 (1) (2015) 199–207.

    Article  Google Scholar 

  17. A. Maghsoodi, A. Ohadi, M. Sadighi and H. Amindavar, Damage detection in multilayered fiber–metal laminates using guided-wave phased array, Journal of Mechanical Science and Technology, 30 (5) (2016) 2113–2120.

    Article  Google Scholar 

  18. N. I. Kim, H. Kim and J. Lee, Damage detection of truss structures using two-stage optimization based on micro genetic algorithm, Journal of Mechanical Science and Technology, 28 (9) (2014) 3687–3695.

    Article  Google Scholar 

  19. J. Xiang and M. Liang, A two-step approach to multidamage detection for plate structures, Engineering Fracture Mechanics, 91 (2012) 73–86.

    Article  Google Scholar 

  20. Z. B. Yang, X. F. Chen, Y. Xie, H. H. Miao, J. J. Gao and K. Z. Qi, Hybrid two -step method of damage detection for plate -like structures, Structural Control and Health Monitoring, 23 (2) (2016) 267–285.

    Article  Google Scholar 

  21. J. Xiang and M. Liang, Wavelet -based detection of beam cracks using modal shape and frequency measurements, Computer - Aided Civil and Infrastructure Engineering, 27 (6) (2012) 439–454.

    Article  Google Scholar 

  22. J. Xiang, T. Matsumoto, J. Long, Y. Wang and Z. Jiang, A simple method to detect cracks in beam-like structures, Smart Structures and Systems, 9 (4) (2012) 335–353.

    Article  Google Scholar 

  23. A. Pandey and M. Biswas, Damage detection in structures using changes in flexibility, Journal of Sound and Vibration, 169 (1) (1994) 3–17.

    Article  MATH  Google Scholar 

  24. F. Au, Y. Cheng, L. Tham and Z. Bai, Structural damage detection based on a micro-genetic algorithm using incomplete and noisy modal test data, Journal of Sound and Vibration, 259 (5) (2003) 1081–1094.

    Article  Google Scholar 

  25. J. Carvalho, B. N. Datta, A. Gupta and M. Lagadapati, A direct method for model updating with incomplete measured data and without spurious modes, Mechanical Systems and Signal Processing, 21 (7) (2007) 2715–2731.

    Article  Google Scholar 

  26. M. Mousavi and A. H. Gandomi, A hybrid damage detection method using dynamic-reduction transformation matrix and modal force error, Engineering Structures, 111 (2016) 425–434.

    Article  Google Scholar 

  27. S. Mirjalili, S. M. Mirjalili and A. Lewis, Grey wolf optimizer, Advances in Engineering Software, 69 (2014) 46–61.

    Article  Google Scholar 

  28. R. V. Rao, V. J. Savsani and D. P. Vakharia, Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems, Computer-Aided Design, 43 (3) (2011) 303–315.

    Article  Google Scholar 

  29. X. S. Yang, M. Karamanoglu and X. He, Flower pollination algorithm: a novel approach for multiobjective optimization, Engineering Optimization, 46 (9) (2014) 1222–1237.

    Article  MathSciNet  Google Scholar 

  30. R. Perera, A. Ruiz and C. Manzano, Performance assessment of multicriteria damage identification genetic algorithms, Computers & Structures, 87 (1) (2009) 120–127.

    Article  Google Scholar 

  31. A. Kaveh and T. Bakhshpoori, Water evaporation optimization: a novel physically inspired optimization algorithm, Computers & Structures, 167 (2016) 69–85.

    Article  Google Scholar 

  32. A. Kaveh and T. Bakhshpoori, An accelerated water evaporation optimization formulation for discrete optimization of skeletal structures, Computers & Structures, 177 (2016) 218–228.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran

    Seyed Rohollah Hoseini Vaez & Narges Fallah

Authors
  1. Seyed Rohollah Hoseini Vaez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Narges Fallah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seyed Rohollah Hoseini Vaez.

Additional information

Recommended by Associate Editor Daeil Kwon

Seyed Rohollah Hoseini Vaez is currently an Assistant Professor at the University of Qom. He teaches courses on the finite element methods, structural optimization, advanced reinforced concrete structures and earthquake engineering. Dr. Hoseini Vaez’s research interests include damage detection, finite element method, optimization algorithms and soft computing.

Narges Fallah received B.Sc. degree in civil engineering from Qom University, Iran, in 2014 and a M.Sc. in 2016 in structural engineering. She is currently a Ph.D. student in Structural Engineering at the University of Qom. Fallah’s research interests include SHM and metaheuristic algorithms.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hoseini Vaez, S.R., Fallah, N. Damage identification of a 2D frame structure using two-stage approach. J Mech Sci Technol 32, 1125–1133 (2018). https://doi.org/10.1007/s12206-018-0215-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-018-0215-8

Keywords

Search

Navigation