Skip to main content
SpringerLink
Log in

Review on acoustic emission source location, damage recognition and lifetime prediction of fiber-reinforced composites

  • Review
  • Published:
Journal of Materials Science Aims and scope Submit manuscript

Abstract

Acoustic emission technology is an effective nondestructive testing method for fiber-reinforced composites, which can monitor the damage process in real time. The main purpose of this paper is to review the information from the various literature articles published on mechanical property and acoustic emission technology of fiber-reinforced composites. It presents a comprehensive review of acoustic emission source location, damage mechanism analysis and life prediction. Initially, several localization methods were introduced in detail under known and unknown sound velocities. More importantly, cluster analysis (unsupervised learning and supervised learning) and waveform processing based on acoustic emission detection technology were discussed. Furthermore, features regarding the prediction of the remaining strength or service life of the composites were listed and explained. Finally, the future development of acoustic emission precise location and intelligent damage pattern recognition were prospected. Starting from the achievable functions, it provides theoretical support for the wider application and further development of the technology.

Graphical abstract

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

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11

Similar content being viewed by others

Abbreviations

NDT:

Nondestructive testing

AE:

Acoustic emission

PAC:

Physical acoustics corporation

TOA:

The time of arrival

CWT:

Continuous wavelet transform

CFRP:

Carbon fiber-reinforced plastic

ANN:

Artificial neural network

ML:

The maximum likelihood

AIC:

Akaike information criterion

LSE:

Least squares estimation

MAE:

Modal acoustic emission

TDOA:

Time difference of arrival

PCT:

Parameter correction technique

SVM:

Support vector machines

PCA:

Principal component analysis

SEM:

Scanning electron microscope

DIC:

Digital image correlation

FCM:

Fuzzy c-means

SOM:

Self-organizing map

KNN:

K nearest neighbor

MLP:

Multilayer perceptron

SVM:

Support vector machine

FFT:

Fast Fourier transform

STFT:

Short time Fourier transform

CWT:

Continuous wavelet transform

WPT:

Wavelet packet transform

HHT:

Hilbert–Huang transform

EMD:

Empirical mode decomposition

References

  1. De Rosa IM, Santulli C, Sarasini F (2009) Acoustic emission for monitoring the mechanical behaviour of natural fibre composites: a literature review. Compos A Appl Sci Manuf 40(9):1456–1469

    Article  Google Scholar 

  2. Faisal NH, Ahmed R, Reuben RL (2013) Indentation testing and its acoustic emission response: applications and emerging trends. Int Mater Rev 56(2):98–142

    Article  Google Scholar 

  3. Muir C, Swaminathan B, Almansour AS, Sevener K, Smith C, Presby M, Kiser JD, Pollock TM, Daly S (2021) Damage mechanism identification in composites via machine learning and acoustic emission. npj Comput Mater 7(1):95

    Article  Google Scholar 

  4. Saeedifar M, Zarouchas D (2020) Damage characterization of laminated composites using acoustic emission: a review. Compos Part B Eng 195:108039

    Article  CAS  Google Scholar 

  5. Barile C, Casavola C, Pappalettera G, Kannan VP (2020) Application of different acoustic emission descriptors in damage assessment of fiber reinforced plastics: a comprehensive review. Eng Fract Mech 235:107083

    Article  Google Scholar 

  6. Gholizadeh S, Leman Z, Baharudin BTHT (2015) A review of the application of acoustic emission technique in engineering. Struct Eng Mech 54(6):1075–1095

    Article  Google Scholar 

  7. Hassan F, Mahmood AKB, Yahya N, Saboor A, Abbas MZ, Khan Z, Rimsan M (2021) State-of-the-art review on the acoustic emission source localization techniques. IEEE Access 9:101246–101266

    Article  Google Scholar 

  8. Ciaburro G, Iannace G (2022) Machine-learning-based methods for acoustic emission testing: a review. Appl Sci 12(20):10476

    Article  CAS  Google Scholar 

  9. Karthik MK, Kumar CS (2022) A comprehensive review on damage characterization in polymer composite laminates using acoustic emission monitoring. Russ J Nondestruct Test 58(8):705–721

    Article  Google Scholar 

  10. Al-Jumaili SK, Eaton MJ, Holford KM, Pearson MR, Crivelli D, Pullin R (2018) Characterisation of fatigue damage in composites using an acoustic emission parameter correction technique. Compos Part B Eng 151:237–244

    Article  CAS  Google Scholar 

  11. Fotouhi M, Najafabadi MA (2014) Acoustic emission-based study to characterize the initiation of delamination in composite materials. J Thermoplast Compos Mater 29(4):519–537

    Article  Google Scholar 

  12. Shahkhosravi NA, Yousefi J, Najafabadi MA, Burvill C, Minak G (2019) Fatigue life reduction of GFRP composites due to delamination associated with the introduction of functional discontinuities. Compos Part B Eng 163:536–547

    Article  CAS  Google Scholar 

  13. Woo S-C, Goo NS (2009) Effect of electric cyclic loading on fatigue cracking of a bending piezoelectric hybrid composite actuator. Compos Sci Technol 69(11–12):1764–1771

    Article  CAS  Google Scholar 

  14. Leone FA, Ozevin D, Awerbuch J, Tan T-M (2012) Detecting and locating damage initiation and progression in full-scale sandwich composite fuselage panels using acoustic emission. J Compos Mater 47(13):1643–1664

    Article  Google Scholar 

  15. Han B-H, Yoon D-J, Huh Y-H, Lee Y-S (2013) Damage assessment of wind turbine blade under static loading test using acoustic emission. J Intell Mater Syst Struct 25(5):621–630

    Article  Google Scholar 

  16. Saeedifar M, Fotouhi M, Najafabadi MA, Toudeshky HH, Minak G (2016) Prediction of quasi-static delamination onset and growth in laminated composites by acoustic emission. Compos Part B Eng 85:113–122

    Article  CAS  Google Scholar 

  17. Zhang Y, Shi J, Zheng J (2021) A method of fracture toughness JIC measurement based on digital image correlation and acoustic emission technique. Mater Des 197:109258

    Article  CAS  Google Scholar 

  18. Han K-N, Zhou W, Qin R, Wang G-F, Ma L-H (2020) Effects of carbon nanotubes on open-hole carbon fiber reinforced polymer composites. Mater Today Commun 24:101106

    Article  CAS  Google Scholar 

  19. Qin R, Zhou W, Han K-N, Zhang Y-J, Ma L-H (2020) Comparison on mechanical properties, damage evolution and aging effects of multi-delaminated composites under three point bending. SN Appl Sci 2(9):1596

    Article  Google Scholar 

  20. Han W, Hu K, Shi Q, Zhu F (2020) Damage evolution analysis of open-hole tensile laminated composites using a progress damage model verified by AE and DIC. Compos Struct 247:112452

    Article  Google Scholar 

  21. Crivelli D, Guagliano M, Eaton M, Pearson M, Al-Jumaili S, Holford K, Pullin R (2015) Localisation and identification of fatigue matrix cracking and delamination in a carbon fibre panel by acoustic emission. Compos Part B Eng 74:1–12

    Article  CAS  Google Scholar 

  22. Romhány G, Czigány T, Karger-Kocsis J (2017) Failure assessment and evaluation of damage development and crack growth in polymer composites via localization of acoustic emission events: a review. Polym Rev 57(3):397–439

    Article  Google Scholar 

  23. Tang J, Soua S, Mares C, Gan T-H (2016) An experimental study of acoustic emission methodology for in service condition monitoring of wind turbine blades. Renew Energy 99:170–179

    Article  Google Scholar 

  24. Gangadharan R, Prasanna G, Bhat MR, Murthy CRL, Gopalakrishnan S (2009) Acoustic emission source location in composite structure by Voronoi construction using geodesic curve evolution. J Acoust Soc Am 126(5):2324–2330

    Article  CAS  Google Scholar 

  25. Liang D, Yuan S-F, Liu M-L (2013) Distributed coordination algorithm for impact location of preciseness and real-time on composite structures. Measurement 46(1):527–536

    Article  Google Scholar 

  26. Fu T, Liu Y, Lau K-T, Leng J (2014) Impact source identification in a carbon fiber reinforced polymer plate by using embedded fiber optic acoustic emission sensors. Compos Part B Eng 66:420–429

    Article  CAS  Google Scholar 

  27. Ciampa F, Meo M (2010) A new algorithm for acoustic emission localization and flexural group velocity determination in anisotropic structures. Compos A Appl Sci Manuf 41(12):1777–1786

    Article  Google Scholar 

  28. Ciampa F, Meo M, Barbieri E (2012) Impact localization in composite structures of arbitrary cross section. Struct Health Monit Int J 11(6):643–655

    Article  Google Scholar 

  29. Caprino G, Lopresto V, Leone C, Papa I (2011) Acoustic emission source location in unidirectional carbon-fiber-reinforced plastic plates with virtually trained artificial neural networks. J Appl Polym Sci 122(6):3506–3513

    Article  CAS  Google Scholar 

  30. Leone C, Lopresto V, Papa I, Caprino G (2012) Triangulation method as a valid tool to locate the damage in unidirectional CFRP laminates. Compos Struct 94(8):2418–2423

    Article  Google Scholar 

  31. De Simone ME, Ciampa F, Boccardi S, Meo M (2017) Impact source localisation in aerospace composite structures. Smart Mater Struct 26(12):125026

    Article  Google Scholar 

  32. Vaghefi RM, Buehrer RM (2013) Asynchronous time-of-arrival-based source localization. In: 2013 IEEE international conference on acoustics, speech and signal processing (ICASSP)

  33. Annibale P, Rabenstein R (2013) Closed-form estimation of the speed of propagating waves from time measurements. Multidimens Syst Signal Process 25(2):361–378

    Article  Google Scholar 

  34. Asamene K, Hudson L, Sundaresan M (2015) Influence of attenuation on acoustic emission signals in carbon fiber reinforced polymer panels. Ultrasonics 59:86–93

    Article  CAS  Google Scholar 

  35. Wang L, Liu Y, Fu W, Li F, Zhao Z, Yu K (2017) Source location using an optimized microfiber coupler sensor based on modal acoustic emission method. Struct Control Health Monit 24(11):e2011

    Article  Google Scholar 

  36. Aljets D, Chong A, Wilcox S (2010) Acoustic emission source location in plate-like structures using a closely arranged triangular sensor array. J Acoust Emiss 28:85–98

    Google Scholar 

  37. Aljets D, Chong A, Wilcox S, Holford K (2012) Acoustic emission source location on large plate-like structures using a local triangular sensor array. Mech Syst Signal Process 30:91–102

    Article  Google Scholar 

  38. Rajic N, Rosalie C, Vien BS, van der Velden S, Rose LRF, Smithard J, Chiu WK (2020) In situ wavenumber-frequency modal decomposition of acoustic emissions. Struct Health Monit 19(6):2033–2050

    Article  Google Scholar 

  39. Sen N, Kundu T (2022) A new signal energy-based approach to acoustic source localization in orthotropic plates: a numerical study. Mech Syst Signal Process 171:108843

    Article  Google Scholar 

  40. Sen N, Kundu T (2018) A new wave front shape-based approach for acoustic source localization in an anisotropic plate without knowing its material properties. Ultrasonics 87:20–32

    Article  Google Scholar 

  41. Sen N, Gawroński M, Packo P, Uhl T, Kundu T (2021) Square-shaped sensor clusters for acoustic source localization in anisotropic plates by wave front shape-based approach. Mech Syst Signal Process 153:107489

    Article  Google Scholar 

  42. Xiao D, He T, Pan Q, Liu X, Wang J, Shan Y (2014) A novel acoustic emission beamforming method with two uniform linear arrays on plate-like structures. Ultrasonics 54(2):737–745

    Article  Google Scholar 

  43. Kalafat S, Sause MGR (2015) Acoustic emission source localization by artificial neural networks. Struct Health Monit 14(6):633–647

    Article  Google Scholar 

  44. Fu T, Zhang Z, Liu Y, Leng J (2015) Development of an artificial neural network for source localization using a fiber optic acoustic emission sensor array. Struct Health Monit 14(2):168–177

    Article  Google Scholar 

  45. Hua S (2016) Acoustic emission source positioning research of 3D braided composite material based on the wavelet network. Funct Mater 23(2):331–336

    Article  Google Scholar 

  46. Sause MGR, Schmitt S, Hoeck B, Monden A (2019) Acoustic emission based prediction of local stress exposure. Compos Sci Technol 17:390–98

    Google Scholar 

  47. Ding G, Xiu C, Wan Z, Li J, Pei X, Zheng Z (2019) Location of tensile damage source of carbon fiber braided composites based on two-step method. Molecules 24(19):3524

    Article  CAS  Google Scholar 

  48. Koabaz M, Hajzargarbashi T, Kundu T, Deschamps M (2011) Locating the acoustic source in an anisotropic plate. Struct Health Monit Int J 11(3):315–323

    Article  Google Scholar 

  49. Ciampa F, Meo M (2011) Impact detection in anisotropic materials using a time reversal approach. Struct Health Monit 11(1):43–49

    Article  Google Scholar 

  50. Ciampa F, Meo M (2011) Acoustic emission localization in complex dissipative anisotropic structures using a one-channel reciprocal time reversal method. J Acoust Soc Am 130(1):168–175

    Article  Google Scholar 

  51. Dong L, Zou W, Sun D, Tong X, Li X, Shu W (2019) Some developments and new insights for microseismic/acoustic emission source localization. Shock Vib 2019:1–15

    Google Scholar 

  52. Nakatani H, Kundu T, Takeda N (2014) Improving accuracy of acoustic source localization in anisotropic plates. Ultrasonics 54(7):1776–1788

    Article  Google Scholar 

  53. Kundu T, Park WH, Packo P, Kundu T (2017) Acoustic source localization in an anisotropic plate without knowing its material properties: a new approach. Health Monit Struct Biol Syst 79:9–17

    Google Scholar 

  54. Sen N, Kundu T (2020) Acoustic source localization in a highly anisotropic plate with unknown orientation of its axes of symmetry and material properties with numerical verification. Ultrasonics 100:105977

    Article  Google Scholar 

  55. Zhou J, Mathews VJ, Adams DO (2019) Acoustic emission-based impact location estimation on composite structures. Struct Health Monit 18(5–6):1652–1668

    Article  Google Scholar 

  56. Kalteremidou KA, Murray BR, Carrella-Payan D, Cernescu A, Van Hemelrijck D, Pyl L (2021) Failure analysis of CF/epoxy hollow beam components using digital image correlation and acoustic emission analyses. Compos Struct 275:114481

    Article  CAS  Google Scholar 

  57. Baxter MG, Pullin R, Holford KM, Evans SL (2007) Delta T source location for acoustic emission. Mech Syst Signal Process 21(3):1512–1520

    Article  Google Scholar 

  58. Eaton MJ, Pullin R, Holford KM (2012) Acoustic emission source location in composite materials using delta T mapping. Compos A Appl Sci Manuf 43(6):856–863

    Article  Google Scholar 

  59. Al-Jumaili SK, Holford KM, Eaton MJ, Pullin R (2015) Parameter correction technique (PCT): a novel method for acoustic emission characterisation in large-scale composites. Compos B Eng 75:336–344

    Article  Google Scholar 

  60. Kim KR, Lee YS (2014) Acoustic emission source localization in plate-like structures using least-squares support vector machines with delta t feature. J Mech Sci Technol 28(8):3013–3020

    Article  Google Scholar 

  61. Al-Jumaili SK, Holford KM, Eaton MJ, McCrory JP, Pearson MR, Pullin R (2014) Classification of acoustic emission data from buckling test of carbon fibre panel using unsupervised clustering techniques. Struct Health Monit 14(3):241–251

    Article  Google Scholar 

  62. Kubiak T, Samborski S, Teter A (2015) Experimental investigation of failure process in compressed channel-section GFRP laminate columns assisted with the acoustic emission method. Compos Struct 133:921–929

    Article  Google Scholar 

  63. Skoczylas J, Samborski S, Kłonica M (2021) A multilateral study on the FRP Composite’s matrix strength and damage growth resistance. Compos Struct 263:113752

    Article  CAS  Google Scholar 

  64. Rzeczkowski J (2020) An experimental analysis of the end-notched flexure composite laminates beams with elastic couplings. Contin Mech Thermodyn 33(6):2331–2343

    Article  Google Scholar 

  65. Rzeczkowski J, Samborski S (2022) Experimental and numerical research of delamination process in CFRP laminates with bending-twisting elastic couplings. Materials (Basel) 15(21):7745

    Article  CAS  Google Scholar 

  66. Zhou W, Han K-N, Qin R, Zhang Y-J (2019) Investigation of mechanical behavior and damage of three-dimensional braided carbon fiber composites. Mater Res Express 6(8):085624

    Article  CAS  Google Scholar 

  67. Tabrizi IE, Kefal A, Zanjani JSM, Akalin C, Yildiz M (2019) Experimental and numerical investigation on fracture behavior of glass/carbon fiber hybrid composites using acoustic emission method and refined zigzag theory. Compos Struct 223:110971

    Article  Google Scholar 

  68. Ali HQ, Emami Tabrizi I, Khan RMA, Tufani A, Yildiz M (2019) Microscopic analysis of failure in woven carbon fabric laminates coupled with digital image correlation and acoustic emission. Compos Struct 230:111515

    Article  Google Scholar 

  69. Ben Ameur M, El Mahi A, Rebiere J-L, Gimenez I, Beyaoui M, Abdennadher M, Haddar M (2019) Investigation and identification of damage mechanisms of unidirectional carbon/flax hybrid composites using acoustic emission. Eng Fract Mech 216:106511

    Article  Google Scholar 

  70. Pan ZB, Zhou W, Zhang K, Ma LH, Liu J (2022) Flexural damage and failure behavior of 3D printed continuous fiber composites by complementary nondestructive testing technology. Polym Compos 43(5):2864–2877

    Article  CAS  Google Scholar 

  71. Zhou W, Zhao WZ, Zhang YN, Ding ZJ (2018) Cluster analysis of acoustic emission signals and deformation measurement for delaminated glass fiber epoxy composites. Compos Struct 195:349–358

    Article  Google Scholar 

  72. Alia A, Fantozzi G, Godin N, Osmani H, Reynaud P (2019) Mechanical behaviour of jute fibre-reinforced polyester composite: characterization of damage mechanisms using acoustic emission and microstructural observations. J Compos Mater 53(24):3377–3394

    Article  CAS  Google Scholar 

  73. Özaslan E, Yetgin A, Acar B, Güler MA (2021) Damage mode identification of open hole composite laminates based on acoustic emission and digital image correlation methods. Compos Struct 274:114299

    Article  Google Scholar 

  74. Xu P, Zhou Z, Liu T, Mal A (2021) Determination of geometric role and damage assessment in hybrid fiber metal laminate (FML) joints based on acoustic emission. Compos Struct 270:114068

    Article  CAS  Google Scholar 

  75. Ma LH, Zhang K, Pan ZB, Zhou W, Liu J (2022) Experimental investigation on the mechanical behavior and damage of 3D printed composites under three-point bending. J Compos Mater 56(7):1019–1037

    Article  CAS  Google Scholar 

  76. Rzeczkowski J, Samborski S, de Moura M (2020) Experimental investigation of delamination in composite continuous fiber-reinforced plastic laminates with elastic couplings. Materials (Basel) 13(22):5146

    Article  CAS  Google Scholar 

  77. Zhao WZ, Zhou W (2019) Cluster analysis of acoustic emission signals and tensile properties of carbon/glass fiber–reinforced hybrid composites. Struct Health Monit 18(5–6):1686–1697

    Article  Google Scholar 

  78. Boussetta H, Beyaoui M, Laksimi A, Walha L, Haddar M (2017) Study of the filament wound glass/polyester composite damage behavior by acoustic emission data unsupervised learning. Appl Acoust 127:175–183

    Article  Google Scholar 

  79. Zanjani JSM, Okan BS, Yilmaz C, Menceloglu Y, Yildiz M (2017) Monitoring the interface and bulk self-healing capability of tri-axial electrospun fibers in glass fiber reinforced epoxy composites. Compos Part A Appl Sci Manuf 99:221–232

    Article  Google Scholar 

  80. Jefferson Andrew J, Arumugam V, Bull DJ, Dhakal HN (2016) Residual strength and damage characterization of repaired glass/epoxy composite laminates using A.E. and D.I.C. Compos Struct 152:124–139

    Article  Google Scholar 

  81. Oz FE, Ersoy N, Lomov SV (2017) Do high frequency acoustic emission events always represent fibre failure in CFRP laminates? Compos A Appl Sci Manuf 103:230–235

    Article  CAS  Google Scholar 

  82. Jefferson Andrew J, Arumugam V (2017) Effect of patch hybridization on the tensile behavior of patch repaired glass/epoxy composite laminates using acoustic emission monitoring. Int J Adhes Adhes 74:155–166

    Article  CAS  Google Scholar 

  83. Li L, Swolfs Y, Straumit I, Yan X, Lomov SV (2015) Cluster analysis of acoustic emission signals for 2D and 3D woven carbon fiber/epoxy composites. J Compos Mater 50(14):1921–1935

    Article  Google Scholar 

  84. Pashmforoush F, Fotouhi M, Ahmadi M (2011) Damage characterization of glass/epoxy composite under three-point bending test using acoustic emission technique. J Mater Eng Perform 21(7):1380–1390

    Article  Google Scholar 

  85. Yousefi J, Ahmadi M, Shahri MN, Oskouei AR, Moghadas FJ (2013) Damage categorization of glass/epoxy composite material under mode II delamination using acoustic emission data: a clustering approach to elucidate wavelet transformation analysis. Arab J Sci Eng 39(2):1325–1335

    Article  Google Scholar 

  86. Assarar M, Bentahar M, El Mahi A, El Guerjouma R (2014) Monitoring of damage mechanisms in sandwich composite materials using acoustic emission. Int J Damage Mech 24(6):787–804

    Article  Google Scholar 

  87. Pashmforoush F, Fotouhi M, Ahmadi M (2012) Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm. J Reinf Plast Compos 31(10):671–680

    Article  CAS  Google Scholar 

  88. Pashmforoush F, Khamedi R, Fotouhi M, Hajikhani M, Ahmadi M (2014) Damage classification of sandwich composites using acoustic emission technique and k-means genetic algorithm. J Nondestruct Eval 33(4):481–492

    Article  Google Scholar 

  89. Fallahi N, Nardoni G, Heidary H, Palazzetti R, Yan XT, Zucchelli A (2016) Supervised and non-supervised AE data classification of nanomodified CFRP during DCB tests. FME Trans 44(4):415–421

    Article  Google Scholar 

  90. Bohmann T, Schlamp M, Ehrlich I (2018) Acoustic emission of material damages in glass fibre-reinforced plastics. Compos B Eng 155:444–451

    Article  CAS  Google Scholar 

  91. Sause MGR, Gribov A, Unwin AR, Horn S (2012) Pattern recognition approach to identify natural clusters of acoustic emission signals. Pattern Recognit Lett 33(1):17–23

    Article  Google Scholar 

  92. Lorriot T, Wargnier H, Wahl JC, Proust A, Lagunegrand L (2013) An experimental criterion to detect onset of delamination in real time. J Compos Mater 48(18):2175–2189

    Article  Google Scholar 

  93. Sawan HA, Walter ME, Marquette B (2015) Unsupervised learning for classification of acoustic emission events from tensile and bending experiments with open-hole carbon fiber composite samples. Compos Sci Technol 107:89–97

    Article  CAS  Google Scholar 

  94. Li L, Lomov SV, Yan X, Carvelli V (2014) Cluster analysis of acoustic emission signals for 2D and 3D woven glass/epoxy composites. Compos Struct 116:286–299

    Article  Google Scholar 

  95. Crivelli D, Guagliano M, Monici A (2014) Development of an artificial neural network processing technique for the analysis of damage evolution in pultruded composites with acoustic emission. Compos B Eng 56:948–959

    Article  CAS  Google Scholar 

  96. Monti A, El Mahi A, Jendli Z, Guillaumat L (2016) Mechanical behaviour and damage mechanisms analysis of a flax-fibre reinforced composite by acoustic emission. Compos A Appl Sci Manuf 90:100–110

    Article  CAS  Google Scholar 

  97. Zhou W, Zhang P-F, Zhang Y-N (2018) Acoustic emission based on cluster and sentry function to monitor tensile progressive damage of carbon fiber woven composites. Appl Sci 8(11):2265

    Article  CAS  Google Scholar 

  98. Tang J, Soua S, Mares C, Gan TH (2017) A pattern recognition approach to acoustic emission data originating from fatigue of wind turbine blades. Sensors (Basel) 17(11):2507

    Article  Google Scholar 

  99. Roundi W, El Mahi A, El Gharad A, Rebiere J-L (2018) Acoustic emission monitoring of damage progression in glass/epoxy composites during static and fatigue tensile tests. Appl Acoust 132:124–134

    Article  Google Scholar 

  100. Yilmaz C, Akalin C, Gunal I, Celik H, Buyuk M, Suleman A, Yildiz M (2018) A hybrid damage assessment for E-and S-glass reinforced laminated composite structures under in-plane shear loading. Compos Struct 186:347–354

    Article  Google Scholar 

  101. Zarif Karimi N, Minak G, Kianfar P (2015) Analysis of damage mechanisms in drilling of composite materials by acoustic emission. Compos Struct 131:107–114

    Article  Google Scholar 

  102. Heidary H, Karimi NZ, Ahmadi M, Rahimi A, Zucchelli A (2014) Clustering of acoustic emission signals collected during drilling process of composite materials using unsupervised classifiers. J Compos Mater 49(5):559–571

    Article  Google Scholar 

  103. Yousefi J, Najfabadi MA, Toudeshky HH, Akhlaghi M (2017) Damage evaluation of laminated composite material using a new acoustic emission lamb-based and finite element techniques. Appl Compos Mater 25(5):1021–1040

    Article  Google Scholar 

  104. de Oliveira R, Marques AT (2008) Health monitoring of FRP using acoustic emission and artificial neural networks. Comput Struct 86(3–5):367–373

    Article  Google Scholar 

  105. Kalogiannakis G, Quintelier J, De Baets P, Degrieck J, Van Hemelrijck D (2008) Identification of wear mechanisms of glass/polyester composites by means of acoustic emission. Wear 264(3–4):235–244

    Article  CAS  Google Scholar 

  106. Torres-Arredondo MA, Tibaduiza DA, McGugan M, Toftegaard H, Borum KK, Mujica LE, Rodellar J, Fritzen CP (2013) Multivariate data-driven modelling and pattern recognition for damage detection and identification for acoustic emission and acousto-ultrasonics. Smart Mater Struct 22(10):105023

    Article  Google Scholar 

  107. Saeedifar M, Najafabadi MA, Zarouchas D, Toudeshky HH, Jalalvand M (2018) Clustering of interlaminar and intralaminar damages in laminated composites under indentation loading using acoustic emission. Compos B Eng 144:206–219

    Article  CAS  Google Scholar 

  108. Chelliah SK, Parameswaran P, Ramasamy S, Vellayaraj A, Subramanian S (2018) Optimization of acoustic emission parameters to discriminate failure modes in glass-epoxy composite laminates using pattern recognition. Struct Health Monit 18(4):1253–1267

    Article  Google Scholar 

  109. Bhat C, Bhat MR, Murthy CRL (2008) Characterization of failure modes in CFRP composites: an ANN approach. J Compos Mater 42(3):257–276

    Article  CAS  Google Scholar 

  110. Gutkin R, Green CJ, Vangrattanachai S, Pinho ST, Robinson P, Curtis PT (2011) On acoustic emission for failure investigation in CFRP: pattern recognition and peak frequency analyses. Mech Syst Signal Process 25(4):1393–1407

    Article  Google Scholar 

  111. Wu H, Yu Z, Wang Y (2019) Experimental study of the process failure diagnosis in additive manufacturing based on acoustic emission. Measurement 136:445–453

    Article  Google Scholar 

  112. Refahi Oskouei A, Heidary H, Ahmadi M, Farajpur M (2012) Unsupervised acoustic emission data clustering for the analysis of damage mechanisms in glass/polyester composites. Mater Des 37:416–422

    Article  CAS  Google Scholar 

  113. Fotouhi M, Sadeghi S, Jalalvand M, Ahmadi M (2016) Analysis of the damage mechanisms in mixed-mode delamination of laminated composites using acoustic emission data clustering. J Thermoplast Compos Mater 30(3):318–340

    Article  Google Scholar 

  114. Arumugam V, Kumar SB, Stanley AJ (2012) Effect of fuzzy C means technique in failure mode discrimination of glass/epoxy laminates using acoustic emission monitoring. Russ J Nondestruct Test 47(12):858–864

    Article  Google Scholar 

  115. Fotouhi M, Heidary H, Ahmadi M, Pashmforoush F (2012) Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clustering. J Compos Mater 46(15):1795–1808

    Article  Google Scholar 

  116. Mohammadi R, Najafabadi MA, Saeedifar M, Yousefi J, Minak G (2017) Correlation of acoustic emission with finite element predicted damages in open-hole tensile laminated composites. Compos B Eng 108:427–435

    Article  Google Scholar 

  117. Shateri M, Ghaib M, Svecova D, Thomson D (2017) On acoustic emission for damage detection and failure prediction in fiber reinforced polymer rods using pattern recognition analysis. Smart Mater Struct 26(6):065023

    Article  Google Scholar 

  118. Sayar H, Azadi M, Ghasemi-Ghalebahman A, Jafari SM (2018) Clustering effect on damage mechanisms in open-hole laminated carbon/epoxy composite under constant tensile loading rate, using acoustic emission. Compos Struct 204:1–11

    Article  Google Scholar 

  119. Azadi M, Sayar H, Ghasemi-Ghalebahman A, Jafari SM (2019) Tensile loading rate effect on mechanical properties and failure mechanisms in open-hole carbon fiber reinforced polymer composites by acoustic emission approach. Compos B Eng 158:448–458

    Article  CAS  Google Scholar 

  120. Barile C, Casavola C, Pappalettera G, Vimalathithan PK (2021) Multiparameter approach for damage propagation analysis in fiber-reinforced polymer composites. Appl Sci 11(1):393

    Article  CAS  Google Scholar 

  121. Ji X-L, Zhou W, Sun H, Liu J, Ma L-H (2022) Damage evolution behavior of bi-adhesive repaired composites under bending load by acoustic emission and micro-CT. Compos Struct 279:114742

    Article  CAS  Google Scholar 

  122. Zhao G, Zhang L, Tang C, Hao W, Luo Y (2019) Clustering of AE signals collected during torsional tests of 3D braiding composite shafts using PCA and FCM. Compos B Eng 161:547–554

    Article  CAS  Google Scholar 

  123. Mahdian A, Yousefi J, Nazmdar M, Zarif Karimi N, Ahmadi M, Minak G (2016) Damage evaluation of laminated composites under low-velocity impact tests using acoustic emission method. J Compos Mater 51(4):479–490

    Article  Google Scholar 

  124. Saeedifar M, Saleh MN, De Freitas ST, Zarouchas D (2019) Damage characterization of adhesively-bonded Bi-material joints using acoustic emission. Compos B Eng 176:107356

    Article  CAS  Google Scholar 

  125. Momon S, Godin N, Reynaud P, R’Mili M, Fantozzi G (2012) Unsupervised and supervised classification of AE data collected during fatigue test on CMC at high temperature. Compos A Appl Sci Manuf 43(2):254–260

    Article  CAS  Google Scholar 

  126. Ech-Choudany Y, Assarar M, Scida D, Morain-Nicolier F, Bellach B (2017) Unsupervised clustering for building a learning database of acoustic emission signals to identify damage mechanisms in unidirectional laminates. Appl Acoust 123:123–132

    Article  Google Scholar 

  127. Nair A, Cai CS, Kong X (2019) Studying failure modes of GFRP laminate coupons using AE pattern-recognition method. J Aerosp Eng 32(4):04019031

    Article  Google Scholar 

  128. Wirtz SF, Beganovic N, Söffker D (2018) Investigation of damage detectability in composites using frequency-based classification of acoustic emission measurements. Struct Health Monit 18(4):1207–1218

    Article  Google Scholar 

  129. Huang J, Hu Q, Song Z, Zhang G, Qin CZ, Wu M, Wang X (2021) Classification of cracking sources of different engineering media via machine learning. Fatigue Fract Eng Mater Struct 44(9):2475–2488

    Article  Google Scholar 

  130. Wang Z, Dixit P, Chegdani F, Takabi B, Tai BL, El Mansori M, Bukkapatnam S (2020) Bidirectional gated recurrent deep learning neural networks for smart acoustic emission sensing of natural fiber-reinforced polymer composite machining process. Smart Sustain Manuf Syst 4(2):179–198

    Article  Google Scholar 

  131. Hong T, Jason WU, Pike M, Schaefer J, Rongzhong LI (2017) Machine learning for acoustic emission signatures in composite laminates. American Society for Composites, Chicago, November 2017

  132. Skoczylas J, Kłonica M, Samborski S (2022) A study on the FRP composite’s matrix damage resistance by means of elastic wave propagation analysis. Compos Struct 297:115935

    Article  CAS  Google Scholar 

  133. Samborski S, Gliszczynski A, Rzeczkowski J, Wiacek N (2019) Mode I interlaminar fracture of glass/epoxy unidirectional laminates. Part I: experimental studies. Materials (Basel) 12(10):1607

    Article  CAS  Google Scholar 

  134. Sause MGR, Horn S (2010) Simulation of acoustic emission in planar carbon fiber reinforced plastic specimens. J Nondestruct Eval 29(2):123–142

    Article  Google Scholar 

  135. Woo S-C, Kim T-W (2014) High-strain-rate impact in Kevlar-woven composites and fracture analysis using acoustic emission. Compos B Eng 60:125–136

    Article  CAS  Google Scholar 

  136. Babu MR, Prakash TVB (2014) Characterisation of fiber failure mode in T-700 carbon fiber reinforced epoxy composites by acoustic emission testing. Russ J Nondestruct Test 50(1):45–57

    Article  Google Scholar 

  137. Bak KM, Kalaichelvan K, Jothilingam A, RajendraBoopathy S (2015) Acoustic emission characterization of failure modes of single-lap joints in glass/epoxy specimens. J Compos Mater 50(1):3–23

    Google Scholar 

  138. Heidary H, Ahmadi M, Rahimi A, Minak G (2012) Wavelet-based acoustic emission characterization of residual strength of drilled composite materials. J Compos Mater 47(23):2897–2908

    Article  Google Scholar 

  139. Bak KM, Kalaichelvan K, Arumugam V (2013) A novel approach for classification of failure modes in single lap joints using acoustic emission data. J Compos Mater 48(24):3003–3017

    Article  Google Scholar 

  140. Woo S, Choi N (2007) Analysis of fracture process in single-edge-notched laminated composites based on the high amplitude acoustic emission events. Compos Sci Technol 67(7–8):1451–1458

    Article  Google Scholar 

  141. Woo S, Goo N (2007) Analysis of the bending fracture process for piezoelectric composite actuators using dominant frequency bands by acoustic emission. Compos Sci Technol 67(7–8):1499–1508

    Article  CAS  Google Scholar 

  142. Kumar CS, Arumugam V, Sajith S, Dhakal HN, John R (2015) Acoustic emission characterisation of failure modes in hemp/epoxy and glass/epoxy composite laminates. J Nondestruct Eval 34(4):1–11

    Article  Google Scholar 

  143. Han W, Gu A, Zhou J (2019) A damage modes extraction method from AE signal in composite laminates based on DEEMD. J Nondestruct Eval 38(3):70

    Article  Google Scholar 

  144. Zhang Z, Xiao Y, Su Z, Pan Y (2018) Continuous monitoring of tightening condition of single-lap bolted composite joints using intrinsic mode functions of acoustic emission signals: a proof-of-concept study. Struct Health Monit 18(4):1219–1234

    Article  Google Scholar 

  145. Dastjerdi PB, Ahmadi M (2018) Characterizing the damage mechanisms in mode II delamination in glass/epoxy composite using acoustic emission. Struct Eng Mech 67(5):545–553

    Google Scholar 

  146. Fotouhi M, Saeedifar M, Sadeghi S, Najafabadi MA, Minak G (2015) Investigation of the damage mechanisms for mode I delamination growth in foam core sandwich composites using acoustic emission. Struct Health Monit 14(3):265–280

    Article  Google Scholar 

  147. Ahadi M, Bakhtiar MS (2010) Leak detection in water-filled plastic pipes through the application of tuned wavelet transforms to acoustic emission signals. Appl Acoust 71(7):634–639

    Article  Google Scholar 

  148. Choi N-S, Woo S-C, Rhee K-Y (2007) Effects of fiber orientation on the acoustic emission and fracture characteristics of composite laminates. J Mater Sci 42(4):1162–1168. https://doi.org/10.1007/s10853-006-1445-1

    Article  CAS  Google Scholar 

  149. Woo S-C, Kim T-W (2016) High strain-rate failure in carbon/Kevlar hybrid woven composites via a novel SHPB-AE coupled test. Compos B Eng 97:317–328

    Article  CAS  Google Scholar 

  150. Jang B-W, Kim C-G (2017) Real-time detection of low-velocity impact-induced delamination onset in composite laminates for efficient management of structural health. Compos B Eng 123:124–135

    Article  CAS  Google Scholar 

  151. Arumugam V, Sajith S, Stanley AJ (2011) Acoustic emission characterization of failure modes in GFRP laminates under mode I delamination. J Nondestruct Eval 30(3):213–219

    Article  Google Scholar 

  152. Arumugam V, Kumar CS, Santulli C, Sarasini F, Stanley AJ (2012) Identification of failure modes in composites from clustered acoustic emission data using pattern recognition and wavelet transformation. Arab J Sci Eng 38(5):1087–1102

    Article  Google Scholar 

  153. Liu X, Yao X, Cai J, Zeng J, Chiu W, Xu J (2021) Failure mode analysis of carbon fiber composite laminates by acoustic emission signals. Adv Mater Sci Eng 202:11–12

    Google Scholar 

  154. Skal’skii VR, Stankevich EM, Matviiv YY (2013) A study of the features of the macrofracturing of composite materials. Russ J Nondestruct Test 49(10):562–571

    Article  Google Scholar 

  155. Dahmene F, Yaacoubi S, El Mountassir M, Bendaoud N, Langlois C, Bardoux O (2016) On the modal acoustic emission testing of composite structure. Compos Struct 140:446–452

    Article  Google Scholar 

  156. Baccar D, Söffker D (2017) Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients. Mech Syst Signal Process 96:77–87

    Article  Google Scholar 

  157. Satour A, Montrésor S, Bentahar M, Elguerjouma R, Boubenider F (2013) Acoustic emission signal denoising to improve damage analysis in glass fibre-reinforced composites. Nondestruct Test Eval 29(1):65–79

    Article  Google Scholar 

  158. Bak KM, KalaiChelvan K, Vijayaraghavan GK, Sridhar BTN (2012) Acoustic emission wavelet transform on adhesively bonded single-lap joints of composite laminate during tensile test. J Reinf Plast Compos 32(2):87–95

    Article  Google Scholar 

  159. Hao W, Yuan Z, Tang C, Zhang L, Zhao G, Luo Y (2019) Acoustic emission monitoring of damage progression in 3D braiding composite shafts during torsional tests. Compos Struct 208:141–149

    Article  Google Scholar 

  160. Barile C, Casavola C, Pappalettera G (2019) Acoustic emission waveform analysis in CFRP under Mode I test. Eng Fract Mech 210:408–413

    Article  Google Scholar 

  161. Barile C, Casavola C, Pappalettera G, Vimalathithan PK (2019) Experimental wavelet analysis of acoustic emission signal propagation in CFRP. Eng Fract Mech 210:400–407

    Article  Google Scholar 

  162. Skal’s’kyi VR, Stankevych OM, Kuz’ IS (2018) Application of wavelet transforms for the analysis of acoustic-emission signals accompanying fracture processes in materials (a survey). Mater Sci 54(2):139–153

    Article  Google Scholar 

  163. Xu D, Liu PF, Chen ZP (2021) Damage mode identification and singular signal detection of composite wind turbine blade using acoustic emission. Compos Struct 255:112954

    Article  Google Scholar 

  164. Saeedifar M, Najafabadi MA, Zarouchas D, Toudeshky HH, Jalalvand M (2018) Barely visible impact damage assessment in laminated composites using acoustic emission. Compos B Eng 152:180–192

    Article  CAS  Google Scholar 

  165. Barile C, Casavola C, Pappalettera G, Vimalathithan PK (2019) Damage characterization in composite materials using acoustic emission signal-based and parameter-based data. Compos B Eng 178:107469

    Article  CAS  Google Scholar 

  166. Siracusano G, Lamonaca F, Tomasello R, Garescì F, Corte AL, Carnì DL, Carpentieri M, Grimaldi D, Finocchio G (2016) A framework for the damage evaluation of acoustic emission signals through Hilbert–Huang transform. Mech Syst Signal Process 75:109–122

    Article  Google Scholar 

  167. Hamdi SE, Le Duff A, Simon L, Plantier G, Sourice A, Feuilloy M (2013) Acoustic emission pattern recognition approach based on Hilbert–Huang transform for structural health monitoring in polymer-composite materials. Appl Acoust 74(5):746–757

    Article  Google Scholar 

  168. Ma P, Sun B, Gu B (2011) Impact tension damage mechanism analyses of co-woven-knitted composite from Hilbert–Huang transform. Int J Damage Mech 21(4):493–523

    Article  Google Scholar 

  169. Han WQ, Zhou JY (2013) Acoustic emission characterization methods of damage modes identification on carbon fiber twill weave laminate. Sci China Technol Sci 56(9):2228–2237

    Article  CAS  Google Scholar 

  170. Han WQ, Ying L, Gu AJ, Yuan FG (2015) Damage modes recognition and Hilbert–Huang transform analyses of CFRP laminates utilizing acoustic emission technique. Appl Compos Mater 23(2):155–178

    Google Scholar 

  171. Shahri MN, Yousefi J, Fotouhi M, Najfabadi MA (2015) Damage evaluation of composite materials using acoustic emission features and Hilbert transform. J Compos Mater 50(14):1897–1907

    Article  Google Scholar 

  172. Murray BR, Kalteremidou KA, Carrella-Payan D, Cernescu A, Van Hemelrijck D, Pyl L (2020) Failure characterisation of CF/epoxy V-shape components using digital image correlation and acoustic emission analyses. Compos Struct 236:111797

    Article  Google Scholar 

  173. Carvelli V, Tomaselli VN, Lomov SV, Verpoest I, Witzel V, Broucke BVd (2010) Fatigue and post-fatigue tensile behaviour of non-crimp stitched and unstitched carbon/epoxy composites. Compos Sci Technol 70(15):2216–2224

    Article  CAS  Google Scholar 

  174. Cuadra J, Vanniamparambil PA, Hazeli K, Bartoli I, Kontsos A (2013) Damage quantification in polymer composites using a hybrid NDT approach. Compos Sci Technol 83:11–21

    Article  CAS  Google Scholar 

  175. Jin L, Jin BC, Kar N, Nutt S, Sun B, Gu B (2013) Tension–tension fatigue behavior of layer-to-layer 3-D angle-interlock woven composites. Mater Chem Phys 140(1):183–190

    Article  CAS  Google Scholar 

  176. Bourchak M, Farrow I, Bond I, Rowland C, Menan F (2007) Acoustic emission energy as a fatigue damage parameter for CFRP composites. Int J Fatigue 29(3):457–470

    Article  CAS  Google Scholar 

  177. Carvelli V, Pazmino J, Lomov SV, Bogdanovich AE, Mungalov DD, Verpoest I (2012) Quasi-static and fatigue tensile behavior of a 3D rotary braided carbon/epoxy composite. J Compos Mater 47(25):3195–3209

    Article  Google Scholar 

  178. Karahan M, Lomov SV, Bogdanovich AE, Verpoest I (2011) Fatigue tensile behavior of carbon/epoxy composite reinforced with non-crimp 3D orthogonal woven fabric. Compos Sci Technol 71(16):1961–1972

    Article  CAS  Google Scholar 

  179. Momon S, Moevus M, Godin N, R’Mili M, Reynaud P, Fantozzi G, Fayolle G (2010) Acoustic emission and lifetime prediction during static fatigue tests on ceramic-matrix-composite at high temperature under air. Compos A Appl Sci Manuf 41(7):913–918

    Article  Google Scholar 

  180. de Vasconcellos DS, Sarasini F, Touchard F, Chocinski-Arnault L, Pucci M, Santulli C, Tirillò J, Iannace S, Sorrentino L (2014) Influence of low velocity impact on fatigue behaviour of woven hemp fibre reinforced epoxy composites. Compos B Eng 66:46–57

    Article  Google Scholar 

  181. Eleftheroglou N, Loutas T (2016) Fatigue damage diagnostics and prognostics of composites utilizing structural health monitoring data and stochastic processes. Struct Health Monit 15(4):473–488

    Article  Google Scholar 

  182. Loutas T, Eleftheroglou N, Zarouchas D (2017) A data-driven probabilistic framework towards the in-situ prognostics of fatigue life of composites based on acoustic emission data. Compos Struct 161:522–529

    Article  Google Scholar 

  183. Eleftheroglou N, Zarouchas D, Benedictus R (2020) An adaptive probabilistic data-driven methodology for prognosis of the fatigue life of composite structures. Compos Struct 245:112386

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China (Grant No. 12172117).

Author information

Authors and Affiliations

  1. Non-destructive Testing Laboratory, School of Quality and Technical Supervision, Hebei University, Baoding, 071002, China

    Wei Zhou, Zhi-bo Pan, Jie Wang, Shuai Qiao, Lian-hua Ma, Jia Liu, Xia-ying Ren & Ya-zhao Liang

  2. National & Local Joint Engineering Research Center of Metrology Instrument and System, Hebei University, Baoding, 071002, China

    Wei Zhou, Zhi-bo Pan, Jie Wang, Shuai Qiao, Lian-hua Ma, Jia Liu, Xia-ying Ren & Ya-zhao Liang

  3. Hebei Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding, 071002, China

    Wei Zhou, Zhi-bo Pan, Jie Wang, Shuai Qiao, Lian-hua Ma, Jia Liu, Xia-ying Ren & Ya-zhao Liang

Authors
  1. Wei Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhi-bo Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jie Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shuai Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lian-hua Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jia Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xia-ying Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ya-zhao Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Wei Zhou, Lian-hua Ma or Jia Liu.

Ethics declarations

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Additional information

Handling Editor: Maude Jimenez.

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, W., Pan, Zb., Wang, J. et al. Review on acoustic emission source location, damage recognition and lifetime prediction of fiber-reinforced composites. J Mater Sci 58, 583–607 (2023). https://doi.org/10.1007/s10853-022-08063-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10853-022-08063-1

Search

Navigation