Skip to main content
SpringerLink
Log in

Structural adhesive damage identification of glass curtain wall

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

The feasibility of using vibration transfer rate as damage parameter is studied by simulation. The excitation mode, sensitive measuring point, structural adhesive damage identification and safety state evaluation of hidden frame glass curtain wall (HFGCW) are studied by experiment. The experimental results show that the accurate vibration spectrum can be obtained by using rubber hammer. The edge of glass plate is selected as the measuring point to obtain the accurate vibration transfer rate. The value of change rate of vibration transmissibility increases with the increase in damage degree of structural adhesive. A nondestructive testing method combining vibration transfer rate and discrete wavelet transform (DWT) is proposed, which can identify the degree of structural adhesive damage of HFGCW well. At the same time, the safety status evaluation model based on vibration transfer rate can evaluate the damage degree of structural adhesive of HFGCW.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Data availability

The data in the current study cannot be made public due to further analysis but can be obtained from corresponding authors upon reasonable request.

References

  1. Li, Q., Zhu, X.: Risk identification and its preventive measures of glass curtain wall. Urban Probl. 246(1), 42–46 (2016)

    Google Scholar 

  2. Wang, N., Ma, J., Liu, H.: Influence of structural sealant on mechanical behavior of hidden frame curtain wall. Appl. Mech. Mater. 44–47, 2534–2538 (2011)

    Article  Google Scholar 

  3. Qing, L., Cui, H., Xing, F., et al.: Reasons for glass plate falling in hidden frame glass curtain wall, China Build. Water 17, 18–20 (2013)

    Google Scholar 

  4. Jang, S.J., Yun, H.D., Lee, M.S.: Localization of rattle noise sources in the vehicle underbody using acceleration signals. Arch. Civ. Mech. Eng. 17(1), 65–74 (2017)

    Article  Google Scholar 

  5. Bedon, C., Claudio, A., Salvatore, N.: Safety issues in the seismic design of secondary frameless glass structures. Safety 5(4), 1–31 (2019)

    Article  Google Scholar 

  6. Puga, H., Olmos, B.A., Olmos, L., et al.: Damage assessment of curtain wall glass. J. Phys.: Conf. Ser. 628(1), 012052 (2015)

    Google Scholar 

  7. Wu, H., Zeng, S., Li, Z.: Study on safety evaluation method of glass curtain wall. J. Nat. Disaters 19(5), 96–100 (2010)

    Google Scholar 

  8. Mojˇskerc, B., Kek, T., Grum, J.: Pulse-echo ultrasonic testing of adhesively bonded joints in glass facades. Strojniski Vestnik/J. Mech. Eng. 62(3), 147–153 (2016)

    Article  Google Scholar 

  9. Hong, X., Zhang, B., Liu, Y.: Deep-learning-based guided wave detection for liquid-level state in porcelain bushing type terminal. Struct. Control Health Monit. 28(1), 1–17 (2021)

    Article  Google Scholar 

  10. Hong, X., Liu, Y., Liufu, Y., et al.: Debonding detection in hidden frame supported glass curtain walls using the nonlinear ultrasonic modulation method with piezoceramic transducers. Sensors 18, 1–18 (2018)

    Article  Google Scholar 

  11. Huang, Z.D., Xie, M., Zhao, J., et al.: Rapid evaluation of safety-state in hidden-frame supported glass curtain walls using remote vibration measurement. J. Build. Eng. 19, 91–97 (2018)

    Article  Google Scholar 

  12. Huang, Z.D., Xie, M.W., Chen, C., Du, Y., Zhao, J.H.: Engineering application of a safety-state evaluation model for hidden frame-supported glass curtain walls based on remote vibration. J. Build. Eng. 26, 1–6 (2019)

    Google Scholar 

  13. Miao, Y., Cai, G., Gu, J.: New measurement technology of structural silicone sealant in hidden frame supported glass curtain wall based on FFT power spectrum. In: 2011 international conference on computer distributed control and intelligent environmental monitoring. IEEE, 2011, 92–95

  14. Liu, X., Bao, Y., Song, Y., et al.: Safety evaluation of glass curtain walls by using dynamic method. China Civ. Eng. J. 42(12), 11–15 (2009)

    Google Scholar 

  15. Liu, J.J., Li, J.H., Ding, L., et al.: Research and development in safe inspection and evaluation for existing building curtain walls. Constr. Technol. 42(24), 9–14 (2013)

    Google Scholar 

  16. Liu, X.G., Bao, Y.W.: Safety evaluation for frame supported glass curtain wall based on natural frequency change. J. Shenyang Univ. Technol. 33(5), 595–600 (2011)

    Google Scholar 

  17. Liu, X.G., Bao, Y.W., Qiu, Y., et al.: In-situ detection technology for failure of curtain-wall insulating glass, China Civ. Eng. J. 44(11), 52–58 (2011)

    Google Scholar 

  18. Jang, S.J., Yun, H.D., Lee, M.S.: Effects of stiffening sealant thickness on the structural performance of structural silicone glazing (SSG) sealant connections in curtain wall systems. Arch. Civ. Mech. Eng. 17(1), 65–74 (2017)

    Article  Google Scholar 

  19. Wang, M., Sheng, X.: Combining empirical wavelet transform and transfer matrix or modal superposition to reconstruct responses of structures subject to typical excitations. Mech. Syst. Sig. Process. 163, 1–28 (2022)

    Article  Google Scholar 

  20. Amezquita-Sanchez, J.P., Adeli, H.: Signal processing techniques for vibration-based health monitoring of smart structures. Arch. Comput. Methods Eng. 23, 1–15 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  21. Farrar, C.R., Doebling, S.W., Nix, D.A.: Vibration-based structural damage identification. Philos. Trans. R Soc. A Math. Phys Eng. Sci. 359, 131–149 (2001)

    Article  MATH  Google Scholar 

  22. Newland, D.E.: Wavelet analysis of vibration. Part 1: theory. J. Vib. Acoust. 116, 409–416 (1994)

    Article  Google Scholar 

  23. Lin, J., Zuo, M.: Gearbox fault diagnosis using adaptive wavelet filter. Mech. Syst. Signal Process. 17(6), 1259–1269 (2003)

    Article  Google Scholar 

  24. Abdelelah, A., Ashwin, K.S., Mani, K.K.: Diagnosis of stator fault severity in induction motor based on discrete wavelet analysis. Measurement 182, 1–12 (2021)

    Google Scholar 

  25. Zhao, B., Lei, D., Fu, J., Yang, L., Xu, W.: Experimental study on micro-damage identification in reinforced concrete beam with wavelet packet and DIC method. Constr. Build. Mater. 210, 338–346 (2019)

    Article  Google Scholar 

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

    Article  Google Scholar 

  27. Bao, L., Cao, Y., Zhang, X.: Intelligent identification of structural damage based on the curvature mode and wavelet analysis theory. Adv. Civ. Eng. 2021(2), 1–15 (2021)

    Google Scholar 

  28. Chen, Z.Y., Luo, Y., Gu, J.Z.: New damage detection method of structural silicone sealant in hidden frame supported glass curtain wall based on FFT power spectrum. Sichuan Build. Sci. 35(2), 104–107 (2009)

    Google Scholar 

  29. Zhang, H.: Damage detection in a composite beam using transmittance functions [D]. North Carolina A and T State University (1998)

  30. Zhang, H., Naser, A.S., Schulz, M.J., Pai, P.F.: Health monitoring of composite beams using piezoceramic patches and curvature transmittance functions, pp. 17–20. ASCE, Engineering Mechanics Div (1998)

    Google Scholar 

  31. Maia, N.M.M., Silva, J.M.M., Ribeiro, A.M.R.: The transmissibility concept in multiple degrees of freedom systems. Mech. Syst. Signal Pr. 15(1), 129–137 (2001)

    Article  Google Scholar 

  32. Ding, Y., Li, A.Q.: Structural damage early warning based on vibration testing and wavelet packet analysis. J. Theor. App. Mech-Pol. 38(5), 639–644 (2006)

    Google Scholar 

  33. Seshadrinath, J., Singh, B., Ketan, B.P.: Incipient turn fault detection and condition monitoring of induction machine using analytical wavelet transform. IEEE Trans. Ind. Appl. 50(3), 2235–2242 (2014)

    Article  Google Scholar 

  34. Zhang, H., Schulz, M.J., Ferguson, F., Pai, P.F.: Structural health monitoring using transmittance functions. Mech. Syst. Signal Pr. 13(5), 765–787 (1999)

    Article  Google Scholar 

  35. Luo, W.Q., Fang, Z.H.: Study on damage detection of full-scale frame-concealed glass curtain-walls based on modal curvature. Build. Inform. 44(13), 1–2 (2017)

    MathSciNet  Google Scholar 

  36. Liu, X.G., Bao, Y.W.: Safety evaluation for frame supported glass curtain wall based on modal frequency change. J. Shenyang Univ. Technol. 33(5), 595–600 (2011)

    Google Scholar 

  37. ] 〈http://www.cnsealant.com/product/9.html〉

  38. Bouzida, A., Touhami, O., Ibtiouen, R., Belouchrani, A., Fadel, M., Rezzoug, A.: Fault diagnosis in industrial induction machines through discrete wavelet transform. IEEE Trans. Ind. Electron. 58(9), 4385–4395 (2010)

    Article  Google Scholar 

  39. Faiz, J., Ebrahimi, B.M., Akin, B., Asaie, B.: Criterion function for broken-bar fault diagnosis in induction motor under load variation using wavelet transform. Electromagnetics 29(3), 220–234 (2009)

    Article  Google Scholar 

  40. Vinayak, B.A., Varma, S., Jagadanand, G.: Precise wavelet selection for condition monitoring of inverter-fed induction machine. In: 2017 IEEE international conference on signal processing, informatics, communication and energy systems, SPICES. (2017) 1–4

  41. Haq, M., Bhalla, S., Naqvi, T.: Fatigue damage monitoring of reinforced concrete frames using wavelet transform energy of PZT-based admittance signals. Meas. 164(C), 1–16 (2020)

    Google Scholar 

  42. Teimoori, T., Mahmoudi, M.: Damage detection in connections of steel moment resisting frames using proper orthogonal decomposition and wavelet transform. Measurement 166, 1–19 (2020)

    Article  Google Scholar 

Download references

Funding

This study was funded by the Natural Science Foundation of Hebei Province (Grant No. E2020203084) and the Youth Talent Projects of Colleges in Hebei Province (Grant No.BJ2020021).

Author information

Authors and Affiliations

  1. Key Laboratory of Mechanical Reliability for Heavy Equipments and Large Structures of Hebei Province, Yanshan University, Qinhuangdao, 066004, China

    G. Yang, X. Y. Long, X. X. Wang, X. M. Liu, H. J. Li & Z. L. Liu

  2. State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao, 066004, China

    X. Y. Long

Authors
  1. G. Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. X. Y. Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. X. X. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. X. M. Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. H. J. Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Z. L. Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by GY. The first draft of the manuscript was written by GY and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to H. J. Li.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, G., Long, X.Y., Wang, X.X. et al. Structural adhesive damage identification of glass curtain wall. Nonlinear Dyn 110, 2573–2587 (2022). https://doi.org/10.1007/s11071-022-07692-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-022-07692-0

Keywords

Search

Navigation