Skip to main content

Advertisement

SpringerLink
Log in

Damage Detection of Thin Plates Using GA-PSO Algorithm Based on Modal Data

  • Research Article - Civil Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

In this study, a new approach for detecting damage, its location, and its severity in plate structures using a genetic–particle swarm optimization, which is a hybrid algorithm, is presented. To evaluate the proposed approach, three numerical examples have been simulated; the examples consist of three different plates including an L-shaped two-clamped supported plate, one quarter of a plate with a hole, and a rectangular two-clamped plate. These plate structures have been modeled using thin plate theory, so they are called thin plate. Additionally, dynamic method based on modal data such as natural frequencies and mode shapes is used to formulate objective function. In order to demonstrate the effectiveness of the new proposed approach and the hybrid algorithm, several structures are tested by several different scenarios with and without noise. Then, the scenarios are simulated with genetic and particle swarm optimization algorithms separately. Finally, the obtained results are compared using two sum error indexes which reveal that the results of the hybrid algorithm have less error.

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. Doebling, S.W.; Farrar, C.R.; Prime, M.B.; Shevitz, D.W.: Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review. In: Los Alamos National Lab, NM (United States) (1996)

  2. Lee, E.-T.; Eun, H.-C.: Damage detection of damaged beam by constrained displacement curvature. J. Mech. Sci. Technol. 22(6), 1111–1120 (2008)

    Article  Google Scholar 

  3. Carden, E.P.; Fanning, P.: Vibration based condition monitoring: a review. Struct. Health Monit. 3(4), 355–377 (2004)

    Article  Google Scholar 

  4. Doebling, S.W.; Farrar, C.R.; Prime, M.B.: A summary review of vibration-based damage identification methods. Shock Vib. Dig. 30(2), 91–105 (1998)

    Article  Google Scholar 

  5. Fan, W.; Qiao, P.: Vibration-based damage identification methods: a review and comparative study. Struct. Health Monit. 10(1), 83–111 (2011)

    Article  Google Scholar 

  6. Rytter, A.: Vibration Based Inspection of Civil Engineering Structures, 1993. Aalborg University, Denmark (1993)

    Google Scholar 

  7. Bagheri, A.; Amiri, G.G.; Razzaghi, S.S.: Vibration-based damage identification of plate structures via curvelet transform. J. Sound Vib. 327(3), 593–603 (2009)

    Article  Google Scholar 

  8. Wang, Q.; Deng, X.: Damage detection with spatial wavelets. Int. J. Solids Struct. 36(23), 3443–3468 (1999)

    Article  MATH  Google Scholar 

  9. Yan, Y.; Yam, L.: Online detection of crack damage in composite plates using embedded piezoelectric actuators/sensors and wavelet analysis. Compos. Struct. 58(1), 29–38 (2002)

    Article  Google Scholar 

  10. Rucka, M.; Wilde, K.: Application of continuous wavelet transform in vibration based damage detection method for beams and plates. J. Sound Vib. 297(3), 536–550 (2006)

    Article  Google Scholar 

  11. Kim, M.; Kim, E.; An, Y.; Park, H.; Sohn, H.: Reference-free impedance-based crack detection in plates. J. Sound Vib. 330(24), 5949–5962 (2011)

    Article  Google Scholar 

  12. Fan, W.; Qiao, P.: A 2-D continuous wavelet transform of mode shape data for damage detection of plate structures. Int. J. Solids Struct. 46(25), 4379–4395 (2009)

    Article  MATH  Google Scholar 

  13. Navabian, N.; Bozorgnasab, M.; Taghipour, R.; Yazdanpanah, O.: Damage identification in plate-like structure using mode shape derivatives. Arch. Appl. Mech. 86(5), 819–830 (2015)

  14. Xiang, J.-W.; Matsumoto, T.; Long, J.-Q.; Ma, G.: Identification of damage locations based on operating deflection shape. Nondestruct. Test. Eval. 28(2), 166–180 (2013)

    Article  Google Scholar 

  15. Song, W.; Dyke, S.; Yun, G.; Harmon, T.: Improved damage localization and quantification using subset selection. J. Eng. Mech. 135(6), 548–560 (2009)

    Article  Google Scholar 

  16. Nicknam, A.; Hosseini, M.: Structural damage localization and evaluation based on modal data via a new evolutionary algorithm. Arch. Appl. Mech. 82(2), 191–203 (2012)

    Article  MATH  Google Scholar 

  17. Masoumi, M.; Jamshidi, E.: Damage diagnosis in steel structures with different noise levels via optimization algorithms. Int. J. Steel Struct. 15(3), 557–565 (2015)

    Article  Google Scholar 

  18. Mukhopadhyay, T.; Dey, T.K.; Chowdhury, R.; Chakrabarti, A.: Structural damage identification using response surface-based multi-objective optimization: a comparative study. Arab. J. Sci. Eng. 40(4), 1027–1044 (2015)

    Article  MathSciNet  Google Scholar 

  19. Xiang, J.; Liang, M.: A two-step approach to multi-damage detection for plate structures. Eng. Fract. Mech. 91, 73–86 (2012)

    Article  Google Scholar 

  20. Xiang, J.; Zhong, Y.; Chen, X.; He, Z.: Crack detection in a shaft by combination of wavelet-based elements and genetic algorithm. Int. J. Solids Struct. 45(17), 4782–4795 (2008)

    Article  MATH  Google Scholar 

  21. Jena, P.K.; Parhi, D.R.: A modified particle swarm optimization technique for crack detection in Cantilever Beams. Arab. J. Sci. Eng. 40(11), 3263–3272 (2015)

    Article  Google Scholar 

  22. Zare Hosseinzadeh, A.; Ghodrati Amiri, G.; Koo, K.-Y.: Optimization-based method for structural damage localization and quantification by means of static displacements computed by flexibility matrix. Eng. Optim. 48(4), 543–561 (2016)

    Article  Google Scholar 

  23. Chen, B.; Nagarajaiah, S.: Flexibility-based structural damage identification using Gauss-Newton method. In: The 14th International Symposium on: Smart Structures and Materials and Nondestructive Evaluation and Health Monitoring 2007, pp. 65291L-65291L–65212. International Society for Optics and Photonics

  24. Kaveh, A.; Hoseini Vaez, S.R.; Hoseini, P.; Fallah, N.: Detection of damage in truss structures using Simplified Dolphin Echolocation algorithm based on modal data. Smart Struct. Syst. 18(5), 983–1004 (2016)

    Article  Google Scholar 

  25. Kaveh, A.; Zolghadr, A.: An improved CSS for damage detection of truss structures using changes in natural frequencies and mode shapes. Adv. Eng. Softw. 80, 93–100 (2015)

    Article  Google Scholar 

  26. Boussaïd, I.; Lepagnot, J.; Siarry, P.: A survey on optimization metaheuristics. Inf. Sci. 237, 82–117 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  27. Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press, Ann Arbor (1975)

    MATH  Google Scholar 

  28. Bäck, T.; Schwefel, H.-P.: An overview of evolutionary algorithms for parameter optimization. Evol. Comput. 1(1), 1–23 (1993)

    Article  Google Scholar 

  29. Blickle, T.; Thiele, L.: A comparison of selection schemes used in genetic algorithms. In. TIK-Report (1995)

  30. Beasley, D.; Bull, D.R.; Martin, R.R.: An overview of genetic algorithms: part 2, research topics. Univ. Comput. 15(4), 170–181 (1993)

    Google Scholar 

  31. Beasley, D.; Martin, R.; Bull, D.: An overview of genetic algorithms: part 1. Fundamentals. Univ. Comput. 15, 58–58 (1993)

    Google Scholar 

  32. Michalawicz, Z.: Genetic algorithms \(+\) data structures \(=\) evolution programs. Springer, Berlin (1996)

  33. Kennedy, J.: Particle swarm optimization. In: Encyclopedia of Machine Learning, pp. 760–766. Springer, Berlin (2011)

  34. Clerc, M.; Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1), 58–73 (2002)

    Article  Google Scholar 

  35. Castillo, O.; Melin, P.: Optimization of type-2 fuzzy systems based on bio-inspired methods: a concise review. Inf. Sci. 205, 1–19 (2012)

    Article  Google Scholar 

  36. Thangaraj, R.; Pant, M.; Abraham, A.; Bouvry, P.: Particle swarm optimization: hybridization perspectives and experimental illustrations. Appl. Math. Comput. 217(12), 5208–5226 (2011)

    MATH  Google Scholar 

  37. Eberhart, R.; Simpson, P.; Dobbins, R.: Computational Intelligence PC Tools. Academic Press Professional, Inc, Cambridge (1996)

    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.

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 Detection of Thin Plates Using GA-PSO Algorithm Based on Modal Data. Arab J Sci Eng 42, 1251–1263 (2017). https://doi.org/10.1007/s13369-016-2398-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-016-2398-6

Keywords

Search

Navigation