72
Views
0
CrossRef citations to date
0
Altmetric
Original Articles

Acoustic emission study on damage mechanism of composite materials repaired with bi-adhesive and damage classification model

, , , , &
Pages 1718-1737 | Received 13 Apr 2023, Accepted 10 Oct 2023, Published online: 25 Oct 2023

References

  • Shang X, Marques EAS, Machado JJM, et al. Review on techniques to improve the strength of adhesive. Compos Part B Eng. 2019;177:107363. doi: 10.1016/j.compositesb.2019.107363.
  • Pires L, Quintino L, Miranda RM. Numerical simulation of mono- and bi-adhesive aluminium lap joints. Int J Adhes Adhes. 2006;20(1):19–36. doi: 10.1163/156856106775212387.
  • Gong X-J, Cheng P, Aivazzadeh S, et al. Design and optimization of bonded patch repairs of laminated composite structures. Compos Struct. 2015;123:292–300. doi: 10.1016/j.compstruct.2014.12.048.
  • Akhavan-Safar A, Ramezani F, Delzendehrooy F, et al. A review on bi-adhesive joints: benefits and challenges. Int J Adhes Adhes. 2022;114:103098. doi: 10.1016/j.ijadhadh.2022.103098.
  • Temiz S. Application of bi-adhesive in double-strap joints subjected to bending moment. J Adhes Sci Technol. 2006;20(14):1547–1560. doi: 10.1163/156856106778884262.
  • Ozer H, Oz O. A comparative evaluation of numerical and analytical solutions to the biadhesive single-lap joint. Math Prob Eng. 2014;2014:1–16. doi: 10.1155/2014/852872.
  • Kumar S, Pandey PC. Behaviour of bi-adhesive joints. J Adhes Sci Technol. 2010;24(7):1251–1281. doi: 10.1163/016942409X12561252291982.
  • das Neves PJC, da Silva LFM, Adams RD. Analysis of mixed adhesive bonded joints Part II: parametric study. J Adhes Sci Technol. 2009;23(1):35–61. doi: 10.1163/156856108X336035.
  • Fekirini H, Bouiadjra BB, Belhouari M, et al. Numerical analysis of the performances of bonded composite repair with two adhesive bands in aircraft structures. Compos Struct. 2008;82(1):84–89. doi: 10.1016/j.compstruct.2006.12.004.
  • Farhidzadeh A, Dehghan-Niri E, Salamone S, et al. Monitoring crack propagation in reinforcedconcrete shear walls by acoustic emission. J Sci Eng. 2013;139(12):04013010.
  • De Groot PJ, Wijnen AM, Janssen RB. Real-time frequency determination of acoustic emission for different fracture mechanisms in carbon/epoxy composites. Compos Sci Technol. 1995;55(4):405–412. doi: 10.1016/0266-3538(95)00121-2.
  • Aggelis DG, Barkoula NM, Matikas TE, et al. Acoustic structural health monitoring of composite materials: damage identification and evaluation in cross ply laminates using acoustic emission and ultrasonics. Compos Sci Technol. 2012;72(10):1127–1133. doi: 10.1016/j.compscitech.2011.10.011.
  • Martinez-Jequier J, Gallego A, Suarea E, et al. Real-time damage mechanisms as-sessment in CFRP samples via acoustic emission lamb wave modal analysis. Compos Part B Eng. 2015;68:317–326. doi: 10.1016/j.compositesb.2014.09.002.
  • Fotouhi M, Najafabadi MA. Acoustic emission-based study to characterize the initiation of delamination in composite materials. J Thermoplast Compos Mater. 2016;29(4):519–537. doi: 10.1177/0892705713519811.
  • Wirtz SF, Beganovic N, Söffker D. Investigation of damage detectability in composites using frequency-based classification of acoustic emission measurements. Struct Health Monit. 2019;18(4):1207–1218. doi: 10.1177/1475921718791894.
  • Barile C, Casavola C, Pappalettera G, et al. Experimental wavelet analysis of acoustic emission signal propagation in CFRP. Eng Fract Mech. 2019;210:400–407. doi: 10.1016/j.engfracmech.2018.05.030.
  • WenQin H, Ying L, AiJun G, et al. Damage modes recognition and Hilbert-Huang transform analyses of CFRP laminates utilizing acoustic emission technique. Appl Compos Mater. 2016;23(2):155–178. doi: 10.1007/s10443-015-9454-3.
  • Muir C, Swaminathan B, Fields K, et al. A machine learning framework for damage mechanism identification from acoustic emissions in unidirectional SiC/SiC composites. npj Comput Mater. 2021;7(1):146. doi: 10.1038/s41524-021-00620-7.
  • Muir C, Swaminathan B, Almansour AS, et al. Damage mechanism identification in composites via machine learning and acoustic emission. npj Comput Mater. 2021;7(1):95. doi: 10.1038/s41524-021-00565-x.
  • Xu D, Liu PF, Chen ZP, et al. Achieving robust damage mode identification of adhesive composite joints for wind turbine blade using acoustic emission and machine learning. Compos Struct. 2020;236:111840. doi: 10.1016/j.compstruct.2019.111840.
  • Xu D, Liu PF, Li JG, et al. Damage mode identification of adhesive composite joints under hygrothermal environment using acoustic emission and machine learning. Compos Struct. 2019;211:351–363. doi: 10.1016/j.compstruct.2018.12.051.
  • Zhao WZ, Zhou W. Cluster analysis of acoustic emission signals and tensile properties of carbon/glass fiber-reinforced hybrid composites. Struct Health Monit. 2019;18(5-6):1686–1697. doi: 10.1177/1475921719833467.
  • Han KN, Zhou W, Qin R, et al. Effects of carbon nanotubes on open-hole carbon fiber reinforced polymer composites. Mater Today Commun. 2020;24:101106. doi: 10.1016/j.mtcomm.2020.101106.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.