Skip to main content

Advertisement

Log in

A Hybrid Wavelet Based–Approach and Genetic Algorithm to Detect Damage in Beam-Like Structures without Baseline Data

  • Published:
Experimental Mechanics Aims and scope Submit manuscript

Abstract

This paper proposes an optimized damage identification method in beam-like structures using genetic algorithm (GA) without baseline data. For this purpose, a vibration-based damage identification algorithm using a damage indicator called ‘Relative Wavelet Packet Entropy’ (RWPE) was implemented to determine the location and extent of damage. The procedure does not require vibration signals from an undamaged structure because the method of comparing signals from different locations in the existing state was found to be effective. To ameliorate the algorithm, GA was utilized to identify the best choice for “mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function to optimize the algorithm. This resulted in the high accuracy of the damage identification algorithm. In addition, this method has eliminated the difficulties in selecting the type of mother wavelet function for damage identification purposes. To investigate the robustness and accuracy of the proposed method, numerical examples and experimental cases with different damage depths were considered and conducted. The results demonstrated that the proposed method has great potential in the identification of damage location and depth of cut in beam-like structures since it does not require the recorded data from an undamaged beam as a baseline for damage detection. Moreover, the relationship between damage location and depth of damage has been evaluated and results showed that the algorithm can be applied to actual structures.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Farrar C, Worden K (2007) An introduction to structural health monitoring. Phil Trans R Soc A 365(1851):303–315

    Article  Google Scholar 

  2. Farrar C, Doebling S, Nix D (2001) Vibration–based structural damage identification. Phil Trans R Soc A 359(1778):131–149

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  4. Kim H, Melhem H (2004) Damage detection of structures by wavelet analysis. Eng Struct 26(3):347–362

    Article  Google Scholar 

  5. Chang C-C, Chen L-W (2003) Vibration damage detection of a Timoshenko beam by spatial wavelet based approach. Appl Acoust 64(12):1217–1240

    Article  Google Scholar 

  6. Chang C-C, Chen L-W (2004) Damage detection of cracked thick rotating blades by a spatial wavelet based approach. Appl Acoust 65(11):1095–1111

    Article  Google Scholar 

  7. Chang C-C, Chen L-W (2005) Detection of the location and size of cracks in the multiple cracked beam by spatial wavelet based approach. Mech Syst Signal Proc 19(1):139–155

    Article  Google Scholar 

  8. Gentile A, Messina A (2003) On the continuous wavelet transforms applied to discrete vibrational data for detecting open cracks in damaged beams. Int J Solids Struct 40(2):295–315

    Article  MATH  Google Scholar 

  9. Loutridis S, Douka E, Trochidis A (2004) Crack identification in double-cracked beams using wavelet analysis. J Sound Vib 277(4):1025–1039

    Article  MATH  Google Scholar 

  10. Umesha P, Ravichandran R, Sivasubramanian K (2009) Crack detection and quantification in beams using wavelets. Comput-Aided Civil Infrastruct Eng 24(8):593–607

    Article  Google Scholar 

  11. Ovanesova A, Suarez L (2004) Applications of wavelet transforms to damage detection in frame structures. Eng Struct 26(1):39–49

    Article  Google Scholar 

  12. Bagheri A, Li K, Rizzo P (2013) Reference-free damage detection by means of wavelet transform and empirical mode decomposition applied to Lamb waves. J Intell Mater Syst Struct 24(2):194–208

    Article  Google Scholar 

  13. Chang C-C, Chen L-W (2004) Damage detection of a rectangular plate by spatial wavelet based approach. Appl Acoust 65(8):819–832

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  16. Zhong S, Oyadiji S (2007) Crack detection in simply supported beams without baseline modal parameters by stationary wavelet transform. Mech Syst Signal Process 21(4):1853–1884

    Article  Google Scholar 

  17. Zhong S, Oyadiji S (2011) Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data. Comput Struct 89(1):127–148

    Article  Google Scholar 

  18. Lee S, Yun G, Shang S (2014) Reference-free damage detection for truss bridge structures by continuous relative wavelet entropy method. Struct Health Monit 1475921714522845

  19. Mikami S, Beskhyroun S, Oshima T (2011) Wavelet packet based damage detection in beam-like structures without baseline modal parameters. Struct Infrastruct Eng 7(3):211–227

    Article  Google Scholar 

  20. Castro E, Garcia-Hernandez M, Gallego A (2006) Damage detection in rods by means of the wavelet analysis of vibrations: influence of the mode order. J Sound Vib 296(4):1028–1038

    Article  Google Scholar 

  21. Castro E, Garcia-Hernandez M, Gallego A (2007) Defect identification in rods subject to forced vibrations using the spatial wavelet transform. Appl Acoust 68(6):699–715

    Article  Google Scholar 

  22. Spanos P, Failla G, Santini A, Pappatico M (2006) Damage detection in Euler–Bernoulli beams via spatial wavelet analysis. Struct Control Health Monit 13(1):472–487

    Article  Google Scholar 

  23. Inoue H, Kishimoto K, Shibuya T (1996) Experimental wavelet analysis of flexural waves in beams. Exp Mech 36(3):212–217

    Article  Google Scholar 

  24. Kim H, Melhem H (2003) Fourier and wavelet analyses for fatigue assessment of concrete beams. Exp Mech 43(2):131–140

    Article  Google Scholar 

  25. Han J-G, Ren W-X, Sun Z-S (2005) Wavelet packet based damage identification of beam structures. Int J Solids Struct 42(26):6610–6627

    Article  MATH  Google Scholar 

  26. Ren W-X, Sun Z-S (2008) Structural damage identification by using wavelet entropy. Eng Struct 30(10):2840–2849

    Article  Google Scholar 

  27. Yam L, Yan Y, Jiang J (2003) Vibration-based damage detection for composite structures using wavelet transform and neural network identification. Compos Struct 60(4):403–412

    Article  Google Scholar 

  28. Diao Y-S, Li H-J, Wang Y (2006) A two-step structural damage detection approach based on wavelet packet analysis and neural network. Proceedings of the 5th International Conference on Machine Learning and Cybernetics 3128–3133

  29. Law S, Li X, Zhu X, Chan S (2005) Structural damage detection from wavelet packet sensitivity. Eng Struct 27(9):1339–1348

    Article  Google Scholar 

  30. Cruz P, Salgado R (2009) Performance of vibration‐based damage detection methods in bridges. Comput Aided Civil Infrastruct Eng 24(1):62–79

    Article  Google Scholar 

  31. Vafaei M, Adnan A, Abd Rahman A (2014) A neuro-wavelet technique for seismic damage identification of cantilever structures. Struct Infrastruct Eng (ahead-of-print) 1–19

  32. Haupt R, Haupt S (2004) John Wiley & Sons, New Jersey, USA

  33. Hao H, Xia Y (2002) Vibration-based damage detection of structures by genetic algorithm. J Comput Civil Eng 16(3):222–229

    Article  Google Scholar 

  34. Vakil-Baghmisheh M-T, Peimani M, Sadeghi M, Ettefagh M (2008) Crack detection in beam-like structures using genetic algorithms. Appl Soft Comput 8(2):1150–1160

    Article  Google Scholar 

  35. Rafiee J, Tse P, Harifi A, Sadeghi M (2009) A novel technique for selecting mother wavelet function using an intelli gent fault diagnosis system. Expert Syst Appl 36(3):4862–4875

    Article  Google Scholar 

  36. Neild S, McFadden P, Williams M (2003) A review of time-frequency methods for structural vibration analysis. Eng Struct 25(6):713–728

    Article  Google Scholar 

  37. Mallat S (1999) A wavelet tour of signal processing. Academic, New York, USA

    MATH  Google Scholar 

  38. Daubechies I (1992) Ten lectures on wavelets. SIAM, Philadelphia, USA

    Book  MATH  Google Scholar 

  39. Ren W-X, Sun Z-S, Xia Y, Hao H, Deeks A (2008) Damage identification of shear connectors with wavelet packet energy: laboratory test study. J Struct Eng 134(5):832–841

    Article  Google Scholar 

  40. Shinde A, Hou Z (2005) A wavelet packet based sifting process and its application for structural health monitoring. Struct Health Monit 4(2):153–170

    Article  Google Scholar 

  41. Sun Z, Chang C-C (2007) Vibration based structural health monitoring: wavelet packet transform based solution. Struct Infrastruct Eng 3(4):313–323

    Article  Google Scholar 

  42. Taha M, Noureldin A, Lucero J, Baca T (2006) Wavelet transform for structural health monitoring: a compendium of uses and features. Struct Health Monit 5(3):267–295

    Article  Google Scholar 

  43. Yen G, Lin K-C (2000) Wavelet packet feature extraction for vibration monitoring. IEEE Trans Ind Electron 47(3):650–667

    Article  Google Scholar 

  44. Rosso O, Martin M, Figliola A, Keller K, Plastino A (2006) EEG analysis using wavelet-based information tools. J Neurosci Methods 153(2):163–182

    Article  Google Scholar 

  45. Xia Y, Hao H, Deeks A (2005) Vibration-based damage detection of shear connectors in Nickol river bridge and Balla Balla river bridge. Part II: laboratory study. Australia: School of Civil & Resource Engineering. The University of Western Australia. Australia: School of Civil & Resource Engineering, The University of Western Australia, Report No. ST-05-02

  46. Goldberg D, Holland J (1988) Genetic algorithms and machine learning. Mach Learn 3(2):95–99

    Article  Google Scholar 

  47. Rao M, Srinivas J, Murthy B (2004) Damage detection in vibrating bodies using genetic algorithms. Comput Struct 82(11):963–968

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to express their sincere thanks to the Ministry of Education, Malaysia for the support given through research grants PG222-2014B and UM.C/625/1/HIR/MOHE/ENG/55.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Abdul Razak.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ravanfar, S.A., Abdul Razak, H., Ismail, Z. et al. A Hybrid Wavelet Based–Approach and Genetic Algorithm to Detect Damage in Beam-Like Structures without Baseline Data. Exp Mech 56, 1411–1426 (2016). https://doi.org/10.1007/s11340-016-0181-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11340-016-0181-y

Keywords

Navigation