Skip to main content
SpringerLink
Log in

Structural Health Monitoring of Composite Materials

  • Review article
  • Published:
Archives of Computational Methods in Engineering Aims and scope Submit manuscript

Abstract

Composite materials owing to low density and beneficial properties such as high stiffness, low coefficient of thermal expansion, high mechanical strength, high dimensional stability, good wear resistance, and design flexibility are employed in various fields such as aeronautical, automobile, power generation, civil, and marine engineering etc. Over their course of service, damages can arise in the composite material due to aging, improper service conditions, and erroneous manufacturing and assembly such as inter-laminar voids, porosity, fibre waviness, wrinkles, de-bonding, and delamination. Techniques like structural health monitoring which utilize traditional techniques integrated with sensors to inspect the health of a structure can assist in localization and quantification of several types of damages present in composites based structural models. In this work, several monitoring methods have been reviewed for damage detection including vibration based sensing, embedded sensing, acoustic emissions, lamb wave method, and comparative vacuum monitoring. Several researchers have focused their study on the health monitoring of operational bridges, buildings, and aerospace vehicles for damage detection.

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

Similar content being viewed by others

References

  1. Ochôa PA, Groves RM, Benedictus R (2020) Effects of high-amplitude low-frequency structural vibrations and machinery sound waves on ultrasonic guided wave propagation for health monitoring of composite aircraft primary structures. J Sound Vib. https://doi.org/10.1016/j.jsv.2020.115289

    Article  Google Scholar 

  2. Ko JM, Ni YQ (2005) Technology developments in structural health monitoring of large-scale bridges. Eng Struct 27:1715–1725. https://doi.org/10.1016/j.engstruct.2005.02.021

    Article  Google Scholar 

  3. Baas EJ, Riggio M, Barbosa AR (2021) A methodological approach for structural health monitoring of mass-timber buildings under construction. Constr Build Mater 268:121153. https://doi.org/10.1016/j.conbuildmat.2020.121153

    Article  Google Scholar 

  4. Wu Z, Zhang Q, Cheng L, Hou S, Tan S (2020) The VMTES: application to the structural health monitoring and diagnosis of rotating machines. Renew Energy 162:2380–2396. https://doi.org/10.1016/j.renene.2020.10.021

    Article  Google Scholar 

  5. El Mountassir M, Yaacoubi S, Dahmene F (2020) Reducing false alarms in guided waves structural health monitoring of pipelines: review synthesis and debate. Int J Press Vessel Pip 188:104210. https://doi.org/10.1016/j.ijpvp.2020.104210

    Article  Google Scholar 

  6. Li M, Kefal A, Oterkus E, Oterkus S (2020) Structural health monitoring of an offshore wind turbine tower using iFEM methodology. Ocean Eng 204:107291. https://doi.org/10.1016/j.oceaneng.2020.107291

    Article  Google Scholar 

  7. Carboni M, Crivelli D (2020) An acoustic emission based structural health monitoring approach to damage development in solid railway axles. Int J Fatigue 139:105753. https://doi.org/10.1016/j.ijfatigue.2020.105753

    Article  Google Scholar 

  8. Farrar CR, Worden K (2007) An introduction to structural health monitoring. Philos Trans R Soc A 365:303–315. https://doi.org/10.1098/rsta.2006.1928

    Article  Google Scholar 

  9. Farrar C, Hemez F, Shunk D, Stinemates D, Nadler B (2004) A review of structural health monitoring literature: 1996–2001

  10. Campbell FC (20210) Structural composite materials. ASM International

  11. Jones RM (1998) Mechanics of composite materials. Taylor & Francis

  12. Tanzi MC, Fare S, Candiani G (2019) Foundations of biomaterials engineering. Academic Press

  13. Tanzi MC, Farè S, Candiani G (2019) Organization, structure, and properties of materials. https://doi.org/10.1016/b978-0-08-101034-1.00001-3

  14. Alheety MA, Raoof A, Al-Jibori SA, Karadağ A, Khaleel AI, Akbaş H, Uzun O (2019) Eco-friendly C60-SESMP-Fe3O4 inorganic magnetizable nanocomposite as high-performance adsorbent for magnetic removal of arsenic from crude oil and water samples. Mater Chem Phys 231:292–300. https://doi.org/10.1016/j.matchemphys.2019.04.040

    Article  Google Scholar 

  15. Zhang W, Cai Y, Downum KR, Ma LQ (2004) Arsenic complexes in the arsenic hyperaccumulator Pteris vittata (Chinese brake fern). J Chromatogr A 1043:249–254. https://doi.org/10.1016/j.chroma.2004.05.090

    Article  Google Scholar 

  16. Abd A, Al-Agha A, Alheety M (2016) Addition of some primary and secondary amines to graphene oxide, and studying their effect on increasing its electrical properties. Baghdad Sci J 13:97–114

    Article  Google Scholar 

  17. Majeed AH, Hussain DH, Al-Tikrity ETB, Alheety MA (2020) Poly (o-phenylenediamine-GO-TiO2) nanocomposite: modulation, characterization and thermodynamic calculations on its H2 storage capacity. Chem Data Collect 28:100450. https://doi.org/10.1016/j.cdc.2020.100450

    Article  Google Scholar 

  18. Sinigaglia T, Lewiski F, Santos Martins ME, Mairesse Siluk JC (2017) Production, storage, fuel stations of hydrogen and its utilization in automotive applications—a review. Int J Hydrog Energy 42(2017):24597–24611. https://doi.org/10.1016/j.ijhydene.2017.08.063

    Article  Google Scholar 

  19. Ludwig M, Haberstroh C, Hesse U (2015) Exergy and cost analyses of hydrogen-based energy storage pathways for residual load management. Int J Hydrog Energy 40:11348–11355. https://doi.org/10.1016/j.ijhydene.2015.03.018

    Article  Google Scholar 

  20. Subhi DSM, Khaleel LI, Alheety MA (2020) Preparation, characterization and H2 storage capacity of newly Mn(II), Co(II), Ni(II), Cu(II) and Zn(II) mixed ligand complexes of paracetamol and saccharine. AIP Conf Proc 2213:20306. https://doi.org/10.1063/5.0000077

    Article  Google Scholar 

  21. Awad ZK, Aravinthan T, Zhuge Y, Gonzalez F (2012) A review of optimization techniques used in the design of fibre composite structures for civil engineering applications. Mater Des 33:534–544. https://doi.org/10.1016/j.matdes.2011.04.061

    Article  Google Scholar 

  22. Montalvão D, Maia NMM, Ribeiro AMR (2006) A review of vibration-based structural health monitoring with special emphasis on composite materials. Shock Vib Dig 38:295–324. https://doi.org/10.1177/0583102406065898

    Article  Google Scholar 

  23. Maddalena R, Bonanno L, Balzano B, Tuinea-Bobe C, Sweeney J, Mihai I (2020) A crack closure system for cementitious composite materials using knotted shape memory polymer (k-SMP) fibres. Cem Concr Compos 114:66. https://doi.org/10.1016/j.cemconcomp.2020.103757

    Article  Google Scholar 

  24. Dhanasekaran P, Kalla D, Asmatulu R (2011) Human safety problems in industrial machining of composite materials. Tech Pap Soc Manuf Eng 66:1–8

    Google Scholar 

  25. Patlolla V, Asmatulu R (2013) Recycling and reusing fiber-reinforced composites. Recycl Technol Syst Manag Pract Environ Impact 66:193–207

    Google Scholar 

  26. Qing X, Kumar A, Zhang C, Gonzalez IF, Guo G, Chang FK (2005) A hybrid piezoelectric/fiber optic diagnostic system for structural health monitoring. Smart Mater Struct 14:66. https://doi.org/10.1088/0964-1726/14/3/012

    Article  Google Scholar 

  27. Qing XP, Chan HL, Beard SJ, Kumar A (2006) An active diagnostic system for structural health monitoring of rocket engines. J Intell Mater Syst Struct 17:619–628. https://doi.org/10.1177/1045389X06059956

    Article  Google Scholar 

  28. Attar H, Ehtemam-Haghighi S, Soro N, Kent D, Dargusch MS (2020) Additive manufacturing of low-cost porous titanium-based composites for biomedical applications: advantages, challenges and opinion for future development. J Alloys Compd 827:154263. https://doi.org/10.1016/j.jallcom.2020.154263

    Article  Google Scholar 

  29. Zhang J, Kong L-B, Cai J-J, Li H, Luo Y-C, Kang L (2010) Hierarchically porous nickel hydroxide/mesoporous carbon composite materials for electrochemical capacitors. Microporous Mesoporous Mater 132:154–162. https://doi.org/10.1016/j.micromeso.2010.02.013

    Article  Google Scholar 

  30. Sadasivuni KK, Cabibihan J-J, Deshmukh K, Goutham S, Abubasha MK, Gogoi JP, Klemenoks I, Sakale G, Sekhar BS, Sreekanth PSR, Rao KV, Knite M (2019) A review on porous polymer composite materials for multifunctional electronic applications. Polym Technol Mater 58:1253–1294. https://doi.org/10.1080/03602559.2018.1542729

    Article  Google Scholar 

  31. Rubin AM, Jerina KL (1993) Evaluation of porosity in composite aircraft structures. Compos Eng 3:601–618. https://doi.org/10.1016/0961-9526(93)90085-X

    Article  Google Scholar 

  32. Siver A (2014) Mechanistic effects of porosity on structural composite materials. University of California, Los Angeles

    Google Scholar 

  33. Kessler SS, Spearing SM, Atalla MJ, Cesnik CES, Soutis C (2001) Structural health monitoring in composite materials using frequency response methods. Nondestruct Eval Mater Compos 4336:1. https://doi.org/10.1117/12.435552

    Article  Google Scholar 

  34. Meirovitch L (1975) Elements of vibration analysis. McGraw-Hill. https://books.google.co.in/books?id=XBOoAAAAIAAJ

  35. Zou Y, Tong L, Steven GP (2000) Vibration-based model-dependent damage (delamination) identification and health monitoring for composite structures—a review. J Sound Vib 230:357–378. https://doi.org/10.1006/jsvi.1999.2624

    Article  Google Scholar 

  36. Ratcliffe C, Heider D, Crane R, Krauthauser C, Yoon MK, Gillespie JW (2008) Investigation into the use of low cost MEMS accelerometers for vibration based damage detection. Compos Struct 82:61–70. https://doi.org/10.1016/j.compstruct.2006.11.012

    Article  Google Scholar 

  37. Yoon M, Heider D, Gillespie J Jr, Ratcliffe C, Crane R (2005) Local damage detection using the two-dimensional gapped smoothing method. J Sound Vib J 279:119–139. https://doi.org/10.1016/j.jsv.2003.10.058

    Article  Google Scholar 

  38. Mariani S, Corigliano A, Caimmi F, Bruggi M, Bendiscioli P, De Fazio M (2013) MEMS-based surface mounted health monitoring system for composite laminates. Microelectronics J 44:598–605. https://doi.org/10.1016/j.mejo.2013.03.003

    Article  Google Scholar 

  39. Tang HY, Winkelmann C, Lestari W, La Saponara V (2011) Composite structural health monitoring through use of embedded PZT sensors. J Intell Mater Syst Struct 22:739–755. https://doi.org/10.1177/1045389X11406303

    Article  Google Scholar 

  40. Mariani S, Caimmi F, Bruggi M, Bendiscioli P (2014) Smart sensing of damage in flexible plates through MEMS. Int J Mech Robot Syst 2:67. https://doi.org/10.1504/IJMRS.2014.064359

    Article  Google Scholar 

  41. Masango TP, Philander O, Msomi V (2018) The continuous monitoring of the health of composite structure. J Eng. https://doi.org/10.1155/2018/8260298

    Article  Google Scholar 

  42. Vodicks R, Galea S (1998) Use of PVDF strain sensors for health monitoring of bonded composite patches. In: Def. Sci. Technol. Organ. DSTO-TR-0684. https://doi.org/10.1088/1757-899X/659/1/012085

  43. Zhang H, Galea SC, Chiu WK, Lam YC (1993) An investigation of thin PVDF films as fluctuating-strain-measuring and damage-monitoring devices. Smart Mater Struct 2:208–216. https://doi.org/10.1088/0964-1726/2/4/002

    Article  Google Scholar 

  44. Bar HN, Bhat MR, Murthy CRL (2004) Identification of failure modes in GFRP using PVDF sensors: ANN approach. Compos Struct 65:231–237. https://doi.org/10.1016/j.compstruct.2003.10.019

    Article  Google Scholar 

  45. Yi J, Liang H (2008) A PVDF-based deformation and motion sensor: modeling and experiments. IEEE Sens J 8:384–391. https://doi.org/10.1109/JSEN.2008.917483

    Article  Google Scholar 

  46. Carrino S, Maffezzoli A, Scarselli G (2020) Active SHM for composite pipes using piezoelectric sensors. Mater Today Proc. https://doi.org/10.1016/j.matpr.2019.12.048

    Article  Google Scholar 

  47. Li W, Cho Y, Li X (2013) Comparative study of linear and nonlinear ultrasonic techniques for evaluation thermal damage of tube-like structures. J Korean Soc Nondestruct. Test 33:66. https://doi.org/10.7779/JKSNT.2013.33.1.1

    Article  Google Scholar 

  48. Scarselli G, Ciampa F, Nicassio F, Meo M (2017) Non-linear methods based on ultrasonic waves to analyse disbonds in single lap joints. Proc Inst Mech Eng Part C J Mech Eng Sci. https://doi.org/10.1177/0954406217704222

    Article  Google Scholar 

  49. Fan W, Qiao P (2011) Vibration-based damage identification methods: a review and comparative study. Struct Heal Monit 10:83–111. https://doi.org/10.1177/1475921710365419

    Article  Google Scholar 

  50. Yan YJ, Cheng L, Wu ZY, Yam LH (2007) Development in vibration-based structural damage detection technique. Mech Syst Signal Process 21:2198–2211. https://doi.org/10.1016/j.ymssp.2006.10.002

    Article  Google Scholar 

  51. Tata U, Deshmukh S, Chiao JC, Carter R, Huang H (2009) Bio-inspired sensor skins for structural health monitoring. Smart Mater Struct 18:66. https://doi.org/10.1088/0964-1726/18/10/104026

    Article  Google Scholar 

  52. Jia Y, Sun K, Agosto FJ, Quĩones MT (2006) Design and characterization of a passive wireless strain sensor. Meas Sci Technol 17:2869–2876. https://doi.org/10.1088/0957-0233/17/11/002

    Article  Google Scholar 

  53. Melik R, Perkgoz NK, Unal E, Puttlitz C, Demir HV (2008) Bio-implantable passive on-chip RF-MEMS strain sensing resonators for orthopaedic applications. J Micromech Microeng 18:66. https://doi.org/10.1088/0960-1317/18/11/115017

    Article  Google Scholar 

  54. Suster M, Guo J, Chaimanonart N, Ko WH, Young DJ (2006) A high-performance MEMS capacitive strain sensing system. J Microelectromech Syst 15:1069–1077. https://doi.org/10.1109/JMEMS.2006.881489

    Article  Google Scholar 

  55. Han BG, Yu Y, Han BZ, Ou JP (2008) Development of a wireless stress/strain measurement system integrated with pressure-sensitive nickel powder-filled cement-based sensors. Sens Actuat A Phys 147:536–543. https://doi.org/10.1016/j.sna.2008.06.021

    Article  Google Scholar 

  56. Wang W, Xue X, Fan S, Liu M, Liang Y, Lu M (2020) Development of a wireless and passive temperature-compensated SAW strain sensor. Sens Actuat A Phys 308:112015. https://doi.org/10.1016/j.sna.2020.112015

    Article  Google Scholar 

  57. Alipour A, Unal E, Gokyar S, Demir HV (2017) Development of a distance-independent wireless passive RF resonator sensor and a new telemetric measurement technique for wireless strain monitoring. Sens Actuat A Phys 255:87–93. https://doi.org/10.1016/j.sna.2017.01.010

    Article  Google Scholar 

  58. Zhang Y, Bai L (2015) Rapid structural condition assessment using radio frequency identification (RFID) based wireless strain sensor. Autom Constr 54:1–11. https://doi.org/10.1016/j.autcon.2015.02.013

    Article  Google Scholar 

  59. Chew ZJ, Ruan T, Zhu M (2016) Strain energy harvesting powered wireless sensor node for aircraft structural health monitoring. Procedia Eng 168:1717–1720. https://doi.org/10.1016/j.proeng.2016.11.498

    Article  Google Scholar 

  60. Gasco F, Feraboli P, Braun J, Smith J, Stickler P, Deoto L (2011) Composites: part a wireless strain measurement for structural testing and health monitoring of carbon fiber composites. Compos Part A 42:1263–1274. https://doi.org/10.1016/j.compositesa.2011.05.008

    Article  Google Scholar 

  61. Chung DDL (2001) Electromagnetic interference shielding effectiveness of carbon materials. Carbon N Y 39:279–285. https://doi.org/10.1016/S0008-6223(00)00184-6

    Article  Google Scholar 

  62. Tsotra P, Friedrich K (2003) Electrical and mechanical properties of functionally graded epoxy-resin/carbon fibre composites. Compos Part A Appl Sci Manuf 34:75–82. https://doi.org/10.1016/S1359-835X(02)00181-1

    Article  Google Scholar 

  63. Manzano SA, Hughes D, Correll N (2018) Wireless online impact source localization on a composite. Procedia Manuf 24:319–324. https://doi.org/10.1016/j.promfg.2018.06.021

    Article  Google Scholar 

  64. Kalayci T, Ugur A (2011) Genetic algorithm-based sensor deployment with area priority. Cybern Syst 42:605–620. https://doi.org/10.1080/01969722.2011.634676

    Article  Google Scholar 

  65. Lee SJ, Ahn D, You I, Yoo DY, Kang YS (2020) Wireless cement-based sensor for self-monitoring of railway concrete infrastructures. Autom Constr 119:103323. https://doi.org/10.1016/j.autcon.2020.103323

    Article  Google Scholar 

  66. Han BG, Yu Y, Han BZ, Ou JP (2008) Development of a wireless stress/strain measurement system integrated with pressure-sensitive nickel powder-filled cement-based sensors. Sens Actuat A Phys 147:536–543. https://doi.org/10.1016/j.sna.2008.06.021

    Article  Google Scholar 

  67. Barroca N, Borges LM, Velez FJ, Monteiro F, Górski M, Castro-Gomes J (2013) Wireless sensor networks for temperature and humidity monitoring within concrete structures. Constr Build Mater 40:1156–1166. https://doi.org/10.1016/j.conbuildmat.2012.11.087

    Article  Google Scholar 

  68. Yu A-L, Ji J-J, Wang Y, Sun H-B (2019) Wireless monitoring system for corrosion degree of reinforcement in concrete. J Nanoelectron Optoelectron 14:887–893. https://doi.org/10.1166/jno.2019.2609

    Article  Google Scholar 

  69. Shiraishi M, Kumagai H, Inada H, Okuhara Y, Matsubara H (2005) The SHM system using self-diagnosis material and wireless data measurement device. In: Tomizuka M (ed) Smart struct. mater. 2005 Sensors Smart Struct. Technol. Civil, Mech. Aerosp. Syst. SPIE, pp 187–194. https://doi.org/10.1117/12.599377

  70. Grosse CU, Glaser SD, Krüger M (2006) Condition monitoring of concrete structures using wireless sensor networks and MEMS. In: Tomizuka M, Yun C-B, Giurgiutiu V (eds) Proceedings of the SPIE symposium smart structure materials, San Diego, CA, pp 407–418. https://doi.org/10.1117/12.657303.

  71. Winkelmann C, Tang R, La Saponara V (2008) Influence of embedded structural health monitoring sensors on the mechanical performance of glass/epoxy composites. In: Proceedings of the international SAMPE symposium exhibition, Long Beach, CA

  72. Alexopoulos ND, Bartholome C, Poulin P, Marioli-Riga Z (2010) Structural health monitoring of glass fiber reinforced composites using embedded carbon nanotube (CNT) fibers. Compos Sci Technol 70:260–271. https://doi.org/10.1016/j.compscitech.2009.10.017

    Article  Google Scholar 

  73. Muto N, Arai Y, Shin SG, Matsubara H, Yanagida H, Sugita M, Nakatsuji T (2001) Hybrid composites with self-diagnosing function for preventing fatal fracture. Compos Sci Technol 61:875–883. https://doi.org/10.1016/S0266-3538(00)00165-2

    Article  Google Scholar 

  74. Ding S, Ruan Y, Yu X, Han B, Ni YQ (2019) Self-monitoring of smart concrete column incorporating CNT/NCB composite fillers modified cementitious sensors. Constr Build Mater 201:127–137. https://doi.org/10.1016/j.conbuildmat.2018.12.203

    Article  Google Scholar 

  75. Luo S, Obitayo W, Liu T (2014) SWCNT-thin-film-enabled fiber sensors for lifelong structural health monitoring of polymeric composites—from manufacturing to utilization to failure. Carbon N Y 76:321–329. https://doi.org/10.1016/j.carbon.2014.04.083

    Article  Google Scholar 

  76. Zhao H, Zhang Y, Bradford PD, Zhou Q, Jia Q, Yuan F-G, Zhu Y (2010) Carbon nanotube yarn strain sensors. Nanotechnology 21:305502. https://doi.org/10.1088/0957-4484/21/30/305502

    Article  Google Scholar 

  77. Abot JL, Song Y, Vatsavaya MS, Medikonda S, Kier Z, Jayasinghe C, Rooy N, Shanov VN, Schulz MJ (2010) Delamination detection with carbon nanotube thread in self-sensing composite materials. Compos Sci Technol 70:1113–1119. https://doi.org/10.1016/j.compscitech.2010.02.022

    Article  Google Scholar 

  78. Sebastian J, Schehl N, Bouchard M, Boehle M, Li L, Lagounov A, Lafdi K (2014) Health monitoring of structural composites with embedded carbon nanotube coated glass fiber sensors. Carbon N Y 66:191–200. https://doi.org/10.1016/j.carbon.2013.08.058

    Article  Google Scholar 

  79. Zhang J, Liu J, Zhuang R, Mäder E, Heinrich G, Gao S (2011) Single MWNT-glass fiber as strain sensor and switch. Adv Mater 23:3392–3397. https://doi.org/10.1002/adma.201101104

    Article  Google Scholar 

  80. Luo S, Liu T (2013) Structure–property–processing relationships of single-wall carbon nanotube thin film piezoresistive sensors. Carbon N Y 59:315–324. https://doi.org/10.1016/j.carbon.2013.03.024

    Article  Google Scholar 

  81. Nag-Chowdhury S, Bellegou H, Pillin I, Castro M, Longrais P, Feller JF (2016) Non-intrusive health monitoring of infused composites with embedded carbon quantum piezo-resistive sensors. Compos Sci Technol 123:286–294. https://doi.org/10.1016/j.compscitech.2016.01.004

    Article  Google Scholar 

  82. Pillin I, Castro M, Chowdhury SN, Feller J-F (2016) Robustness of carbon nanotube-based sensor to probe composites’ interfacial damage in situ. J Compos Mater 50:109–113. https://doi.org/10.1177/0021998315571029

    Article  Google Scholar 

  83. Gojny FH, Wichmann MHG, Fiedler B, Bauhofer W, Schulte K (2005) Influence of nano-modification on the mechanical and electrical properties of conventional fibre-reinforced composites. Compos Part A Appl Sci Manuf 36:1525–1535. https://doi.org/10.1016/j.compositesa.2005.02.007

    Article  Google Scholar 

  84. Thostenson ET, Chou TW (2008) Carbon nanotube-based health monitoring of mechanically fastened composite joints. Compos Sci Technol 68:2557–2561. https://doi.org/10.1016/j.compscitech.2008.05.016

    Article  Google Scholar 

  85. Xiao Y, Ishikawa T (2005) Bearing strength and failure behavior of bolted composite joints (part I: experimental investigation). Compos Sci Technol 65:1022–1031. https://doi.org/10.1016/j.compscitech.2005.02.011

    Article  Google Scholar 

  86. Xiao Y, Ishikawa T (2005) Bearing strength and failure behavior of bolted composite joints (part II: modeling and simulation). Compos Sci Technol 65:1032–1043. https://doi.org/10.1016/j.compscitech.2004.12.049

    Article  Google Scholar 

  87. Ladani RB, Wu S, Zhang J, Ghorbani K, Kinloch AJ, Mouritz AP, Wang CH (2017) Using carbon nanofibre sensors for in-situ detection and monitoring of disbonds in bonded composite joints. Procedia Eng 188:362–368. https://doi.org/10.1016/j.proeng.2017.04.496

    Article  Google Scholar 

  88. Lim AS, Melrose ZR, Thostenson ET, Chou T-W (2011) Damage sensing of adhesively-bonded hybrid composite/steel joints using carbon nanotubes. Compos Sci Technol 71:1183–1189. https://doi.org/10.1016/j.compscitech.2010.10.009

    Article  Google Scholar 

  89. Mactabi R, Rosca ID, Hoa SV (2013) Monitoring the integrity of adhesive joints during fatigue loading using carbon nanotubes. Compos Sci Technol 78:1–9. https://doi.org/10.1016/j.compscitech.2013.01.020

    Article  Google Scholar 

  90. Zhang W, Sakalkar V, Koratkar N (2007) In situ health monitoring and repair in composites using carbon nanotube additives. Appl Phys Lett 91:133102. https://doi.org/10.1063/1.2783970

    Article  Google Scholar 

  91. Al-Saleh MH, Sundararaj U (2009) A review of vapor grown carbon nanofiber/polymer conductive composites. Carbon N Y 47:2–22. https://doi.org/10.1016/j.carbon.2008.09.039

    Article  Google Scholar 

  92. Hasan MMB, Cherif C, Foisal ABM, Onggar T, Hund RD, Nocke A (2013) Development of conductive coated polyether ether ketone (PEEK) filament for structural health monitoring of composites. Compos Sci Technol 88:76–83. https://doi.org/10.1016/j.compscitech.2013.08.033

    Article  Google Scholar 

  93. Onggar T, Cheng T, Hund H, Hund RD, Cherif C (2011) Metallization of inert polyethylene terephthalate textile materials: wet-chemical silvering with natural and synthetic polyamine, part I. Text Res J 81:2017–2032. https://doi.org/10.1177/0040517511413323

    Article  Google Scholar 

  94. Lu S, Tian C, Wang X, Chen D, Ma K, Leng J, Zhang L (2017) Health monitoring for composite materials with high linear and sensitivity GnPs/epoxy flexible strain sensors. Sens Actuat A Phys 267:409–416. https://doi.org/10.1016/j.sna.2017.10.047

    Article  Google Scholar 

  95. Kim Y-J, Cha JY, Ham H, Huh H, So D-S, Kang I (2011) Preparation of piezoresistive nano smart hybrid material based on graphene. Curr Appl Phys 11:S350–S352. https://doi.org/10.1016/j.cap.2010.11.022

    Article  Google Scholar 

  96. Zha J-W, Zhang B, Li RKY, Dang Z-M (2016) High-performance strain sensors based on functionalized graphene nanoplates for damage monitoring. Compos Sci Technol 123:32–38. https://doi.org/10.1016/j.compscitech.2015.11.028

    Article  Google Scholar 

  97. Steinke K, Groo LA, Sodano HA (2021) Laser induced graphene for in-situ ballistic impact damage and delamination detection in aramid fiber reinforced composites. Compos Sci Technol 202:108551. https://doi.org/10.1016/j.compscitech.2020.108551

    Article  Google Scholar 

  98. Takeda N (2000) Structural health monitoring for smart composite structure systems in Japan. Ann Chim Sci Des Matériaux 25:545–549. https://doi.org/10.1016/S0151-9107(01)80008-8

    Article  Google Scholar 

  99. Satori K, Ikeda Y, Kurosawa Y, Hongo A, Takeda N (2000) Development of small-diameter optical fiber sensors for damage detection in composite laminates. In: Proceedings of the SPIE—International Society Optical Engineering. SPIE, Newport Beach, CA, US, pp 104–111. https://doi.org/10.1117/12.388097

  100. Jones R, Galea S (2002) Health monitoring of composite repairs and joints using optical fibres. Compos Struct 58:397–403. https://doi.org/10.1016/S0263-8223(02)00235-0

    Article  Google Scholar 

  101. Leng J, Asundi A (2003) Structural health monitoring of smart composite materials by using EFPI and FBG sensors. Sens Actuat A Phys 103:330–340. https://doi.org/10.1016/S0924-4247(02)00429-6

    Article  Google Scholar 

  102. Liu T, Brooks D, Martin A, Badcock R, Ralph B, Fernando GF (1997) A multi-mode extrinsic Fabry–Pérot interferometric strain sensor. Smart Mater Struct 6:464–469. https://doi.org/10.1088/0964-1726/6/4/011

    Article  Google Scholar 

  103. Rao Y-J (1997) In-fibre Bragg grating sensors. Meas Sci Technol 8:355–375. https://doi.org/10.1088/0957-0233/8/4/002

    Article  Google Scholar 

  104. Holmes C, Godfrey M, Bull DJ, Dulieu-Barton J (2020) Real-time through-thickness and in-plane strain measurement in carbon fibre reinforced polymer composites using planar optical Bragg gratings. Opt Lasers Eng 133:106111. https://doi.org/10.1016/j.optlaseng.2020.106111

    Article  Google Scholar 

  105. Zhang X, Chen R, Wang A, Xu Y, Jiang Y, Ming H, Zhao W (2019) Monitoring the failure forms of a composite laminate system by using panda polarization maintaining fiber Bragg gratings. Opt Express 27:17571. https://doi.org/10.1364/oe.27.017571

    Article  Google Scholar 

  106. Qiu Y, Wang QB, Zhao HT, Chen JA, Wang YY (2013) Review on composite structural health monitoring based on fiber Bragg grating sensing principle. J Shanghai Jiaotong Univ 18:129–139. https://doi.org/10.1007/s12204-013-1375-4

    Article  Google Scholar 

  107. Zhang L, Shu X, Bennion I (2002) Advances in UV-inscribed fiber grating optic sensor technologies. In: Proceedings of the IEEE sensors, 2002. IEEE, Orlando, USA, pp 31–35. https://doi.org/10.1109/ICSENS.2002.1036982

  108. Grattan KTV, Sun T (2000) Fiber optic sensor technology: an overview. Sens Actuat A Phys 82:40–61. https://doi.org/10.1016/S0924-4247(99)00368-4

    Article  Google Scholar 

  109. Breidne M (1999) Fiber Bragg gratings: a versatile photonics component. In: Proceedings of the SPIE—International Society Optical Engineering. SPIE, pp 104–111. https://doi.org/10.1117/12.373605

  110. Rito RL, Crocombe AD, Ogin SL (2017) Health monitoring of composite patch repairs using CFBG sensors: experimental study and numerical modelling. Compos Part A Appl Sci Manuf 100:255–268. https://doi.org/10.1016/j.compositesa.2017.05.012

    Article  Google Scholar 

  111. Palaniappan J, Wang H, Ogin SL, Thorne A, Reed GT, Tjin SC (2005) Use of conventional and chirped optical fibre Bragg gratings to detect matrix cracking damage in composite materials. J Phys Conf Ser 15:55–60. https://doi.org/10.1088/1742-6596/15/1/010

    Article  Google Scholar 

  112. Okabe Y, Tsuji R, Takeda N (2004) Application of chirped fiber Bragg grating sensors for identification of crack locations in composites. Compos Part A Appl Sci Manuf 35:59–65. https://doi.org/10.1016/j.compositesa.2003.09.004

    Article  Google Scholar 

  113. Palaniappan J, Wang H, Ogin SL, Thorne AM, Reed GT, Crocombe AD, Rech Y, Tjin SC (2007) Changes in the reflected spectra of embedded chirped fibre Bragg gratings used to monitor disbonding in bonded composite joints. Compos Sci Technol 67:2847–2853. https://doi.org/10.1016/j.compscitech.2007.01.028

    Article  Google Scholar 

  114. Kister G, Winter D, Badcock RA, Gebremichael YM, Boyle WJO, Meggitt BT, Grattan KTV, Fernando GF (2007) Structural health monitoring of a composite bridge using Bragg grating sensors. Part 1: evaluation of adhesives and protection systems for the optical sensors. Eng Struct 29:440–448. https://doi.org/10.1016/j.engstruct.2006.05.012

    Article  Google Scholar 

  115. Gebremichael YM, Li W, Boyle WJO, Meggitt BT, Grattan KTV, McKinley B, Fernando GF, Kister G, Winter D, Canning L, Luke S (2005) Integration and assessment of fibre Bragg grating sensors in an all-fibre reinforced polymer composite road bridge. Sens Actuators A Phys 118:78–85. https://doi.org/10.1016/j.sna.2004.08.005

    Article  Google Scholar 

  116. Kister G, Badcock RA, Gebremichael YM, Boyle WJO, Grattan KTV, Fernando GF, Canning L (2007) Monitoring of an all-composite bridge using Bragg grating sensors. Constr Build Mater 21:1599–1604. https://doi.org/10.1016/j.conbuildmat.2006.07.007

    Article  Google Scholar 

  117. Hegde G, Asundi A (2006) Performance analysis of all-fiber polarimetric strain sensor for composites structural health monitoring. NDT E Int 39:320–327. https://doi.org/10.1016/j.ndteint.2005.09.003

    Article  Google Scholar 

  118. Lee KW, Peiyi AC, Chan F, Ho J, Shelly J, Asundi AK, Hegde GM (2003) Sensitivity analysis of all fibers in polarimetric fiber optic sensor for structural health monitoring of composites. Nondestruct Eval Heal Monit Aerosp Mater Compos II(5046):185. https://doi.org/10.1117/12.484294

    Article  Google Scholar 

  119. Rufai O, Chandarana N, Gautam M, Potluri P, Gresil M (2020) Cure monitoring and structural health monitoring of composites using micro-braided distributed optical fibre. Compos Struct 254:112861. https://doi.org/10.1016/j.compstruct.2020.112861

    Article  Google Scholar 

  120. Sánchez DM, Gresil M, Soutis C (2015) Distributed internal strain measurement during composite manufacturing using optical fibre sensors. Compos Sci Technol 120:49–57. https://doi.org/10.1016/j.compscitech.2015.09.023

    Article  Google Scholar 

  121. Guemes A, Fernandez-Lopez A, Fernandez P (2014) Damage detection in composite structures from fibre optic distributed strain measurements. In: 7th European working structural health monitoring, Nantes.

  122. Barrias A, Casas JR, Villalba S (2016) A review of distributed optical fiber sensors for civil engineering applications. Sensors 16:66. https://doi.org/10.3390/s16050748

    Article  Google Scholar 

  123. Rufai O, Gautam M, Potluri P, Gresil M (2019) Optimisation of optical fibre using micro-braiding for structural health monitoring. J Intell Mater Syst Struct 30:171–185. https://doi.org/10.1177/1045389X18810805

    Article  Google Scholar 

  124. Nguyen NQ, Gupta N, Ioppolo T, Ötügen MV (2009) Whispering gallery mode-based micro-optical sensors for structural health monitoring of composite materials. J Mater Sci 44:1560–1571. https://doi.org/10.1007/s10853-008-3163-3

    Article  Google Scholar 

  125. Matsko A, Savchenkov AA, Strekalov D, Ilchenko V, Maleki L (2005) Review of applications of whispering-gallery mode resonators in photonics and nonlinear optics. Interplanet Netw Prog Rep 42:66

    Google Scholar 

  126. Zhi Y, Meldrum A (2014) Tuning a microsphere whispering-gallery-mode sensor for extreme thermal stability. Appl Phys Lett. https://doi.org/10.1063/1.4890961

    Article  Google Scholar 

  127. Ioppolo T, Ötügen MV (2007) Pressure tuning of whispering gallery mode resonators. J Opt Soc Am B 24:2721–2726. https://doi.org/10.1364/JOSAB.24.002721

    Article  Google Scholar 

  128. Laine J-P, Tapalian C, Little B, Haus H (2001) Acceleration sensor based on high-Q optical microsphere resonator and pedestal antiresonant reflecting waveguide coupler. Sens Actuat A Phys 93:1–7. https://doi.org/10.1016/S0924-4247(01)00636-7

    Article  Google Scholar 

  129. Kozhevnikov M, Ioppolo T, Stepaniuk V, Sheverev V, Otugen M (2006) Optical force sensor based on whispering gallery mode resonators. In: 44th AIAA aerospace science meeting exhibition, Reno. https://doi.org/10.2514/6.2006-649

  130. Hegedus G, Sarkadi T, Czigany T (2020) Self-sensing composite: reinforcing fiberglass bundle for damage detection. Compos Part A Appl Sci Manuf 131:105804. https://doi.org/10.1016/j.compositesa.2020.105804

    Article  Google Scholar 

  131. Malik SA, Wang L, Curtis PT, Fernando GF (2016) Self-sensing composites: in-situ detection of fibre fracture. Sensors 16:66. https://doi.org/10.3390/s16050615

    Article  Google Scholar 

  132. Rauf A, Hand RJ, Hayes SA (2012) Optical self-sensing of impact damage in composites using E-glass cloth. Smart Mater Struct 21:45021. https://doi.org/10.1088/0964-1726/21/4/045021

    Article  Google Scholar 

  133. de Groot PJ, Wijnen PAM, Janssen RBF (1995) Real-time frequency determination of acoustic emission for different fracture mechanisms in carbon/epoxy composites. Compos Sci Technol 55:405–412. https://doi.org/10.1016/0266-3538(95)00121-2

    Article  Google Scholar 

  134. Russell SS, Henneke E (1977) Signature analysis of acoustic emission from graphite/epoxy composites

  135. Komai K, Minoshima K, Shibutani T (1990) Investigations of the fracture mechanism of carbon/epoxy composites by AE signal analyses. Trans Japan Soc Mech Eng A 56:1792–1799

    Article  Google Scholar 

  136. Barré S, Benzeggagh ML (1994) On the use of acoustic emission to investigate damage mechanisms in glass-fibre-reinforced polypropylene. Compos Sci Technol 52:369–376. https://doi.org/10.1016/0266-3538(94)90171-6

    Article  Google Scholar 

  137. Morscher GN (1999) Modal acoustic emission of damage accumulation in a woven SiC/SiC composite. Compos Sci Technol 59:687–697. https://doi.org/10.1016/S0266-3538(98)00121-3

    Article  Google Scholar 

  138. Surgeon M, Wevers M (1999) Modal analysis of acoustic emission signals from CFRP laminates. NDT E Int 32:311–322. https://doi.org/10.1016/S0963-8695(98)00077-2

    Article  Google Scholar 

  139. Das S, Chattopadhyay A, Zhou X (2009) Acoustic based structural health monitoring for composites using optimal sensor placement: analysis and experiments. J Reinf Plast Compos 28:83–97. https://doi.org/10.1177/0731684407084099

  140. Carr RD, Greenberg HJ, Hart WE, Phillips CA (2004) Addressing modelling uncertainties in sensor placement for community water systems. In: Critical transitions in water and environmental resources management, pp 1–10. https://doi.org/10.1061/40737(2004)457

  141. Ding Y, Kim P, Ceglarek D, Jin J (2003) Optimal sensor distribution for variation diagnosis in multistation assembly processes. IEEE Trans Robot Autom 19:543–556. https://doi.org/10.1109/TRA.2003.814516

    Article  Google Scholar 

  142. Ganesan D, Cristescu R, Beferull-Lozano B (2004) Power-efficient sensor placement and transmission structure for data gathering under distortion constraints. In: Third international symposium information processing sensors networks. IEEE, pp 142–150. https://doi.org/10.1109/IPSN.2004.238898

  143. Staszewski WJ, Worden K (2001) Overview of optimal sensor location methods for damage detection. In: Rao VS (ed) Smart structure materials 2001 model. Signal process. Control smart structure. SPIE, pp 179–187. https://doi.org/10.1117/12.436472

  144. Worden K, Burrows AP (2001) Optimal sensor placement for fault detection. Eng Struct 23:885–901. https://doi.org/10.1016/S0141-0296(00)00118-8

    Article  Google Scholar 

  145. Fu T, Liu Y, Li Q, Leng J (2009) Fiber optic acoustic emission sensor and its applications in the structural health monitoring of CFRP materials. Opt Lasers Eng 47:1056–1062. https://doi.org/10.1016/j.optlaseng.2009.03.011

    Article  Google Scholar 

  146. Gong J, MacAlpine JMK, Jin W, Liao Y (2001) Locating acoustic emission with an amplitude-multiplexed acoustic sensor array based on a modified Mach-Zehnder interferometer. Appl Opt 40:6199–6202. https://doi.org/10.1364/AO.40.006199

    Article  Google Scholar 

  147. Kim D-H, Koo B-Y, Kim C-G, Hong C-S (2004) Damage detection of composite structures using a stabilized extrinsic Fabry-Perot interferometric sensor system. Smart Mater Struct 13:593–598. https://doi.org/10.1088/0964-1726/13/3/018

    Article  Google Scholar 

  148. Borinski JW, Boyd CD, Dietz JA, Duke JC, Home MR (2001) Fiber optic sensors for predictive health monitoring. In: AUTOTESTCON proceedings, systems readiness technology conference. IEEE, pp 250–262. https://doi.org/10.1109/AUTEST.2001.948969

  149. Yuan L, Zhou L, Jin W (2005) Detection of acoustic emission in structure using Sagnac-like fiber-loop interferometer. Sens Actuat A Phys 118:6–13. https://doi.org/10.1016/j.sna.2004.06.031

    Article  Google Scholar 

  150. Lee J, Kim S (2007) Structural damage detection in the frequency domain using neural networks. J Intell Mater Syst Struct 18:785–792. https://doi.org/10.1177/1045389X06073640

    Article  Google Scholar 

  151. Aggelis DG, Barkoula NM, Matikas TE, Paipetis AS (2012) Acoustic structural health monitoring of composite materials: damage identification and evaluation in cross ply laminates using acoustic emission and ultrasonics. Compos Sci Technol 72:1127–1133. https://doi.org/10.1016/j.compscitech.2011.10.011

    Article  Google Scholar 

  152. Katerelos D, Paipetis A, Loutas T, Sotiriadis G, Kostopoulos V, Ogin S (2009) In situ damage monitoring of cross-ply laminates using acoustic emission. Plast Rubber Compos 38:229–234. https://doi.org/10.1179/174328909X435348

    Article  Google Scholar 

  153. Shiotani T, Ohtsu M, Ikeda K (2001) Detection and evaluation of AE waves due to rock deformation. Constr Build Mater 15:235–246. https://doi.org/10.1016/S0950-0618(00)00073-8

    Article  Google Scholar 

  154. Van Hauwaert A, Thimus J-F, Delannay F (1998) Use of ultrasonics to follow crack growth. Ultrasonics 36:209–217. https://doi.org/10.1016/S0041-624X(97)00129-7

    Article  Google Scholar 

  155. Masmoudi S, El Mahi A, Turki S, el Guerjouma R (2013) Structural health monitoring by acoustic emission of smart composite laminates embedded with piezoelectric sensor. In: Lecture notes mechanical engineering, pp 307–314. https://doi.org/10.1007/978-3-642-37143-1_37

  156. Ye L, Lu Y, Su Z, Meng G (2005) Functionalized composite structures for new generation airframes: a review. Compos Sci Technol 65:1436–1446. https://doi.org/10.1016/j.compscitech.2004.12.015

    Article  Google Scholar 

  157. Godin N, Huguet S, Gaertner R (2005) Integration of the Kohonen’s self-organising map and k-means algorithm for the segmentation of the AE data collected during tensile tests on cross-ply composites. NDT E Int 38:299–309. https://doi.org/10.1016/j.ndteint.2004.09.006

    Article  Google Scholar 

  158. Moevus M, Godin N, R’Mili M, Rouby D, Reynaud P, Fantozzi G, Farizy G (2008) Analysis of damage mechanisms and associated acoustic emission in two SiCf/[Si–B–C] composites exhibiting different tensile behaviours. Part II: unsupervised acoustic emission data clustering. Compos Sci Technol 68:1258–1265. https://doi.org/10.1016/j.compscitech.2007.12.002

    Article  Google Scholar 

  159. Martins AT, Aboura Z, Harizi W, Laksimi A, Khellil K (2019) Structural health monitoring for GFRP composite by the piezoresistive response in the tufted reinforcements. Compos Struct 209:103–111. https://doi.org/10.1016/j.compstruct.2018.10.091

    Article  Google Scholar 

  160. Plain KP, Tong L (2010) The effect of stitch incline angle on mode I fracture toughness—experimental and modelling. Compos Struct 92:1620–1630. https://doi.org/10.1016/j.compstruct.2009.11.027

    Article  Google Scholar 

  161. Colin de Verdiere M, Skordos AA, Walton AC, May M (2012) Influence of loading rate on the delamination response of untufted and tufted carbon epoxy non-crimp fabric composites/Mode II. Eng Fract Mech 96:1–10. https://doi.org/10.1016/j.engfracmech.2011.12.011

    Article  Google Scholar 

  162. Lascoup B, Aboura Z, Khellil K, Benzeggagh M (2010) Impact response of three-dimensional stitched sandwich composite. Compos Struct 92:347–353. https://doi.org/10.1016/j.compstruct.2009.08.012

    Article  Google Scholar 

  163. Xia F, Wu X (2010) Study on impact properties of through-thickness stitched foam sandwich composites. Compos Struct 92:412–421. https://doi.org/10.1016/j.compstruct.2009.08.016

    Article  Google Scholar 

  164. Martins AT, Aboura Z, Harizi W, Laksimi A, Khellil K (2018) Analysis of the impact and compression after impact behavior of tufted laminated composites. Compos Struct 184:352–361. https://doi.org/10.1016/j.compstruct.2017.09.096

    Article  Google Scholar 

  165. Schulte K, Baron C (1989) Load and failure analyses of CFRP laminates by means of electrical resistivity measurements. Compos Sci Technol 36:63–76. https://doi.org/10.1016/0266-3538(89)90016-X

    Article  Google Scholar 

  166. Ceysson O, Salvia M, Vincent L (1996) Damage mechanisms characterisation of carbon fibre/epoxy composite laminates by both electrical resistance measurements and acoustic emission analysis. Scr Mater 34:1273–1280. https://doi.org/10.1016/1359-6462(95)00638-9

    Article  Google Scholar 

  167. Abry JC, Bochard S, Chateauminois A, Salvia M, Giraud G (1999) In situ detection of damage in CFRP laminates by electrical resistance measurements. Compos Sci Technol 59:925–935. https://doi.org/10.1016/S0266-3538(98)00132-8

    Article  Google Scholar 

  168. Zhao Q, Zhang K, Zhu S, Xu H, Cao D, Zhao L, Zhang R, Yin W (2019) Review on the electrical resistance/conductivity of carbon fiber reinforced polymer. Appl Sci 9:66. https://doi.org/10.3390/app9112390

    Article  Google Scholar 

  169. Denghong X, Yong G (2020) Damage monitoring of carbon fiber reinforced silicon carbide composites under random vibration environment by acoustic emission technology. Ceram Int 46:18948–18957. https://doi.org/10.1016/j.ceramint.2020.04.218

    Article  Google Scholar 

  170. Yong G, Denghong X, Tian H, Ye L, Naitian L, Quanhong Y, Yanrong W (2019) Identification of damage mechanisms of carbon fiber reinforced silicon carbide composites under static loading using acoustic emission monitoring. Ceram Int 45:13847–13858. https://doi.org/10.1016/j.ceramint.2019.04.082

    Article  Google Scholar 

  171. Joseph R, Bhuiyan MY, Giurgiutiu V (2019) Acoustic emission from vibration of cracked sheet-metal samples. Eng Fract Mech 217:106544. https://doi.org/10.1016/j.engfracmech.2019.106544

    Article  Google Scholar 

  172. Tan Z-Y, Min C-W, Wu H-W, Qian Y, Li M (2017) Comparison of acoustic emission characteristics for C/SiC composite component under combination of heating and mechanical loading. Acta Metall. Sin. Engl. Lett. 30:66. https://doi.org/10.1007/s40195-017-0564-9

    Article  Google Scholar 

  173. 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 Part B Eng 108:427–435. https://doi.org/10.1016/j.compositesb.2016.09.101

    Article  Google Scholar 

  174. Rose JL (2014) Ultrasonic guided waves in solid media, Illustrate. Cambridge University Press

    Book  Google Scholar 

  175. Prasad SM, Balasubramaniam K, Krishnamurthy CV (2004) Structural health monitoring of composite structures using Lamb wave tomography. Smart Mater Struct. https://doi.org/10.1088/0964-1726/13/5/N01

    Article  Google Scholar 

  176. Subbarao PMV, Munshi P, Muralidhar K (1997) Performance of iterative tomographic algorithms applied to non-destructive evaluation with limited data. NDT E Int 30:359–370. https://doi.org/10.1016/S0963-8695(97)00005-4

    Article  Google Scholar 

  177. Rosalie C, Chan A, Chiu WK, Galea SC, Rose F, Rajic N (2005) Structural health monitoring of composite structures using stress wave methods. Compos Struct 67:157–166. https://doi.org/10.1016/j.compstruct.2004.09.016

    Article  Google Scholar 

  178. Jansen DP, Hutchins DA (1990) Lamb wave tomography. In: Proceedings of the ultrasonics symposium, Honolulu, HI, USA, pp 1017–1020. https://doi.org/10.1109/ULTSYM.1990.171515

  179. Dines KA, Lytle RJ (1979) Computerized geophysical tomography. Proc IEEE 67:1065–1073. https://doi.org/10.1109/PROC.1979.11390

    Article  Google Scholar 

  180. Giurgiutiu V, Santoni-Bottai G (2011) Structural health monitoring of composite structures with piezoelectric-wafer active sensors. AIAA J 49:565–581. https://doi.org/10.2514/1.J050641

    Article  Google Scholar 

  181. Kessler S, Spearing S (2002) Damage detection in composite materials using lamb wave methods. Smart Mater Struct 11:269. https://doi.org/10.1088/0964-1726/11/2/310

    Article  Google Scholar 

  182. Diamanti K, Soutis C, Hodgkinson JM (2005) Non-destructive inspection of sandwich and repaired composite laminated structures. Compos Sci Technol 65:2059–2067. https://doi.org/10.1016/j.compscitech.2005.04.010

    Article  Google Scholar 

  183. Wilcox P, Lowe M, Cawley P (2000) Lamb and SH wave transducer arrays for the inspection of large areas of thick plates. Rev Prog Quant Eval 19:1049–1056. https://doi.org/10.1063/1.1306159

    Article  Google Scholar 

  184. Diamanti K, Soutis C, Hodgkinson JM (2007) Piezoelectric transducer arrangement for the inspection of large composite structures. Compos Part A Appl Sci Manuf 38:1121–1130. https://doi.org/10.1016/j.compositesa.2006.06.011

    Article  Google Scholar 

  185. Giurgiutiu V, Soutis C (2012) Enhanced composites integrity through structural health monitoring. Appl Compos Mater 19:813–829. https://doi.org/10.1007/s10443-011-9247-2

    Article  Google Scholar 

  186. Santoni-Bottai G, Giurgiutiu V (2012) Exact shear-lag solution for guided waves tuning with piezoelectric-wafer active sensors. AIAA J 50:2285–2294. https://doi.org/10.2514/1.J050667

    Article  Google Scholar 

  187. Giurgiutiu (2014) Structural health monitoring with piezoelectric wafer active sensors. Elsevier.

  188. Munian RK, Mahapatra DR, Gopalakrishnan S (2018) Lamb wave interaction with composite delamination. Compos Struct 206:484–498. https://doi.org/10.1016/j.compstruct.2018.08.072

    Article  Google Scholar 

  189. Rokhlin SI (1981) Resonance phenomena of Lamb waves scattering by a finite crack in a solid layer. J Acoust Soc Am 69:922–928. https://doi.org/10.1121/1.385614

    Article  MATH  Google Scholar 

  190. Klepka A, Pieczonka L, Staszewski WJ, Aymerich F (2014) Impact damage detection in laminated composites by non-linear vibro-acoustic wave modulations. Compos Part B Eng 65:99–108. https://doi.org/10.1016/j.compositesb.2013.11.003

    Article  Google Scholar 

  191. Hayashi T, Endoh S (2000) Calculation and visualization of Lamb wave motion. Ultrasonics 38:770–773. https://doi.org/10.1016/S0041-624X(99)00225-5

    Article  Google Scholar 

  192. Hayashi T, Kawashima K (2002) Multiple reflections of Lamb waves at a delamination. Ultrasonics 40:193–197. https://doi.org/10.1016/S0041-624X(02)00136-1

    Article  Google Scholar 

  193. Gorgin R, Luo Y, Wu Z (2020) Environmental and operational conditions effects on Lamb wave based structural health monitoring systems: a review. Ultrasonics 105:106114. https://doi.org/10.1016/j.ultras.2020.106114

    Article  Google Scholar 

  194. Roach D (2009) Real time crack detection using mountable comparative vacuum monitoring sensors. Smart Struct Syst 5:17–328

    Article  Google Scholar 

  195. Roach D, Rackow K (2006) Health monitoring of aircraft structures using distributed sensor systems. In: DoD/NASA/FAA aging aircraft conference, March 6–10

  196. Wishaw M, Barton DP (2001) Comparative vacuum monitoring: A new method of in-situ real-time crack detection and monitoring. In: Proceedings of the 10th Asia-Pacific conference on nondestructive testing, Brisbane, Australia 2001 Sep, pp 18–21

  197. Clark G, Katei S (2001) Evaluation of a novel NDE technique for surface crack monitoring using laboratory fatigue specimens. In: Jeams R (ed) Aeronautics and fatigue digital age

  198. Stehmeier H, Speckmann H (2004) Comparative vacuum monitoring (CVM) monitoring of fatigue cracking in aircraft structures. In: 2nd European workings structure healing and monitoring, Munich, Germany, pp 1–8

  199. Barton DP (2009) Comparative vacuum monitoring (CVMTM). Encycl Struct Heal Monit. https://doi.org/10.1002/9780470061626.shm132

    Article  Google Scholar 

  200. Wheatley G, Kollgaard J, Register J, Zaidi M (2005) Comparative vacuum monitoring (CVM) as an alternate means of compliance (AMOC). Insight 47:153–156

    Article  Google Scholar 

  201. Kousourakis A, Mouritz AP, Bannister MK (2006) Interlaminar properties of polymer laminates containing internal sensor cavities. Compos Struct 75:610–618. https://doi.org/10.1016/j.compstruct.2006.04.086

    Article  Google Scholar 

  202. Bleeck O, Munz D, Schaller W, Yang YY (1998) Effect of a graded interlayer on the stress intensity factor of cracks in a joint under thermal loading. Eng Fract Mech 60:615–623. https://doi.org/10.1016/S0013-7944(98)00044-7

    Article  Google Scholar 

  203. Wisnom MR, Reynolds T, Gwilliam N (1996) Reduction in interlaminar shear strength by discrete and distributed voids. Compos Sci Technol 56:93–101. https://doi.org/10.1016/0266-3538(95)00128-X

    Article  Google Scholar 

  204. de Almeida SFM, dos Santos Nogueira Neto Z (1994) Effect of void content on the strength of composite laminates. Compos Struct 28:139–148. https://doi.org/10.1016/0263-8223(94)90044-2

  205. Afshari SS, Pourtakdoust SH, Crawford BJ, Seethalerc R, Milani AS (2020) Time-varying structural reliability assessment method: application to fiber reinforced composites under repeated impact loading. Compos Struct 6(66):113287. https://doi.org/10.1016/j.compstruct.2020.113287

    Article  Google Scholar 

  206. Xu K, Xie M, Tang LC, Ho SL (2003) Application of neural networks in forecasting engine systems reliability. Appl Soft Comput 2:255–268. https://doi.org/10.1016/S1568-4946(02)00059-5

    Article  Google Scholar 

  207. Wang Z, Huang H-Z, Du L (2011) Reliability analysis on competitive failure processes under fuzzy degradation data. Appl Soft Comput 11:2964–2973. https://doi.org/10.1016/j.asoc.2010.11.018

    Article  Google Scholar 

  208. Li J, Chen JB (2004) Probability density evolution method for dynamic response analysis of structures with uncertain parameters. Comput Mech 34:400–409. https://doi.org/10.1007/s00466-004-0583-8

    Article  MATH  Google Scholar 

  209. Kumar PR, Varaiya P (2015) Stochastic systems: estimation, identification, and adaptive control. SIAM.

  210. Mei Z, Guo Z (2018) Verification of probability density evolution method through shaking table tests of a randomly base-driven structure. Adv Struct Eng 21:514–528. https://doi.org/10.1177/1369433217723412

    Article  Google Scholar 

  211. Grassia L, Iannone M, Califano A, D’Amore A (2019) Strain based method for monitoring the health state of composite structures. Compos Part B Eng 176:107253. https://doi.org/10.1016/j.compositesb.2019.107253

    Article  Google Scholar 

  212. James R, Giurgiutiu V (2020) Towards the generation of controlled one-inch impact damage in thick CFRP composites for SHM and NDE validation. Compos Part B Eng 203:108463. https://doi.org/10.1016/j.compositesb.2020.108463

    Article  Google Scholar 

  213. James R, Giurgiutiu V, Flores M (2020) Challenges of generating controlled one-inch impact damage in thick CFRP composites. In: Proceedings of the AIAA Scitech 2020 Forum, 6–10 January, Orlando, FL, USA. https://doi.org/10.2514/6.2020-0723

  214. Verijenko B, Verijenko V (2005) A new structural health monitoring system for composite laminates. Compos Struct 71:315–319. https://doi.org/10.1016/j.compstruct.2005.09.024

    Article  Google Scholar 

  215. Bhandarkar D, Zackay VF, Parker ER (1972) Stability and mechanical properties of some metastable austenitic steels. Metall Trans 3:2619–2631. https://doi.org/10.1007/BF02644238

    Article  Google Scholar 

  216. Maxwell PC, Goldberg A, Shyne JC (1974) Stress-assisted and strain-induced martensites in Fe–Ni–C alloys. Metall Trans 5:1305–1318. https://doi.org/10.1007/BF02646613

    Article  Google Scholar 

  217. Qin FX, Peng HX (2010) Macro-composites containing ferromagnetic microwires for structural health monitoring, Nano. Commun Netw 1:126–130. https://doi.org/10.1016/j.nancom.2010.08.001

    Article  Google Scholar 

  218. Murray VN (206) Progress in ferromagnetism research, illustrate. Nova Publishers

  219. Patil S, Mallikarjuna Reddy D (2020) Impact damage assessment in carbon fiber reinforced composite using vibration-based new damage index and ultrasonic C-scanning method. Structures 28:638–650. https://doi.org/10.1016/j.istruc.2020.09.011

    Article  Google Scholar 

  220. Tita V, De Carvalho J, Vandepitte D (2008) Failure analysis of low velocity impact on thin composite laminates: experimental and numerical approaches. Compos Struct 83:413–428. https://doi.org/10.1016/j.compstruct.2007.06.003

    Article  Google Scholar 

  221. Yan A-M, Kerschen G, De Boe P, Golinval J-C (2005) Structural damage diagnosis under varying environmental conditions—part II: local PCA for non-linear cases. Mech Syst Signal Process 19:865–880. https://doi.org/10.1016/j.ymssp.2004.12.003

    Article  Google Scholar 

  222. Meruane V, Heylen W (2012) Structural damage assessment under varying temperature conditions. Struct Heal Monit 11:345–357. https://doi.org/10.1177/1475921711419995

    Article  Google Scholar 

  223. Manoach E, Warminski J, Kloda L, Teter A (2017) Numerical and experimental studies on vibration based methods for detection of damage in composite beams. Compos Struct 170:26–39. https://doi.org/10.1016/j.compstruct.2017.03.005

    Article  Google Scholar 

  224. Gul M, Catbas N (2011) Damage assessment with ambient vibration data using a novel time series analysis methodology. J Struct Eng 137:1518–1526. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000366

    Article  Google Scholar 

  225. Goi Y, Kim C-W (2017) Damage detection of a truss bridge utilizing a damage indicator from multivariate autoregressive model. J Civ Struct Heal Monit 7:153–162. https://doi.org/10.1007/s13349-017-0222-y

    Article  Google Scholar 

  226. Silva M, Santos A, Figueiredo E, Santos R, Sales C, Costa JCWA (2016) A novel unsupervised approach based on a genetic algorithm for structural damage detection in bridges. Eng Appl Artif Intell 52:168–180. https://doi.org/10.1016/j.engappai.2016.03.002

    Article  Google Scholar 

  227. Mehrjoo M, Khaji N, Moharrami H, Bahreininejad A (2008) Damage detection of truss bridge joints using artificial neural networks. Expert Syst Appl 35:1122–1131. https://doi.org/10.1016/j.eswa.2007.08.008

    Article  Google Scholar 

  228. Cury A, Crémona C (2012) Pattern recognition of structural behaviors based on learning algorithms and symbolic data concepts. Struct Control Heal Monit 19:161–186. https://doi.org/10.1002/stc.412

    Article  Google Scholar 

  229. Yeung WT, Smith JW (2005) Damage detection in bridges using neural networks for pattern recognition of vibration signatures. Eng Struct 27:685–698. https://doi.org/10.1016/j.engstruct.2004.12.006

    Article  Google Scholar 

  230. Nair A, Cai CS (2010) Acoustic emission monitoring of bridges: review and case studies. Eng Struct 32:1704–1714. https://doi.org/10.1016/j.engstruct.2010.02.020

    Article  Google Scholar 

  231. Gatti M (2019) Structural health monitoring of an operational bridge: a case study. Eng Struct 195:200–209. https://doi.org/10.1016/j.engstruct.2019.05.102

    Article  Google Scholar 

  232. Alampalli S (2019) 17—Structural health monitoring of composite structures for durability. In: Guedes RM (ed) Creep fatigue polymer matrix composites, 2nd ed. Woodhead Publishing, pp 531–558. https://doi.org/10.1016/B978-0-08-102601-4.00017-5

  233. Kilic G (2015) Using advanced NDT for historic buildings: towards an integrated multidisciplinary health assessment strategy. J Cult Herit 16:526–535. https://doi.org/10.1016/j.culher.2014.09.010

    Article  Google Scholar 

  234. Lima HF, da Silva Vicente R, Nogueira RN, Abe I, de Brito Andre PS, Fernandes C, Rodrigues H, Varum H, Kalinowski HJ, Costa A, de Lemos Pinto J (2008) Structural health monitoring of the Church of Santa Casa da MisericÓrdia of Aveiro using FBG sensors. IEEE Sens J 8:1236–1242. https://doi.org/10.1109/JSEN.2008.926177

  235. Boscato G, Dal Cin A, Ientile S, Russo S (2016) Optimized procedures and strategies for the dynamic monitoring of historical structures. J Civ Struct Heal Monit 6:265–289. https://doi.org/10.1007/s13349-016-0164-9

    Article  Google Scholar 

  236. Anastasi G, Re GL, Ortolani M (2009) WSNs for structural health monitoring of historical buildings. In: 2nd Conference human systems interactions. IEEE, pp 574–579. https://doi.org/10.1109/HSI.2009.5091041

  237. Ye XW, Su YH, Han J (2014) Structural health monitoring of civil infrastructure using optical fiber sensing technology: a comprehensive review. Sci World J 2014:652329. https://doi.org/10.1155/2014/652329

    Article  Google Scholar 

  238. Ravi R, Abrar A, Thirumalini S (2019) Alternative approach for traditional slaking and grinding of air lime mortar for restoration of heritage structures: natural polymer. J Archit Eng 25:4019017. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000361

    Article  Google Scholar 

  239. Rafiei MH, Adeli H (2017) A novel machine learning-based algorithm to detect damage in high-rise building structures. Struct Des Tall Spec Build 26:e1400. https://doi.org/10.1002/tal.1400

    Article  Google Scholar 

  240. González MP, Zapico JL (2008) Seismic damage identification in buildings using neural networks and modal data. Comput Struct 86:416–426. https://doi.org/10.1016/j.compstruc.2007.02.021

    Article  Google Scholar 

  241. Bandara R, Chan T, Thambiratnam D (2013) The three-stage artificial neural network method for damage assessment of building structures. Aust J Struct Eng 14:66. https://doi.org/10.7158/S12-036.2013.14.1

    Article  Google Scholar 

  242. Mishra M (2020) Machine learning techniques for structural health monitoring of heritage buildings: a state-of-the-art review and case studies. J Cult Herit. https://doi.org/10.1016/j.culher.2020.09.005

    Article  Google Scholar 

  243. Gopinath V, Ramadoss R (2020) Review on structural health monitoring for restoration of heritage buildings. Mater Today Proc 43:1534–1538. https://doi.org/10.1016/j.matpr.2020.09.318

    Article  Google Scholar 

  244. Pachón P, Infantes M, Cámara M, Compán V, García-Macías E, Friswell MI, Castro-Triguero R (2020) Evaluation of optimal sensor placement algorithms for the Structural Health Monitoring of architectural heritage. Application to the Monastery of San Jerónimo de Buenavista (Seville, Spain). Eng Struct 202:109843. https://doi.org/10.1016/j.engstruct.2019.109843

    Article  Google Scholar 

  245. Pachón P, Castro R, García-Macías E, Compan V, Puertas E (2018) Torroja’s bridge: Tailored experimental setup for SHM of a historical bridge with a reduced number of sensors. Eng Struct 162:11–21. https://doi.org/10.1016/j.engstruct.2018.02.035

    Article  Google Scholar 

  246. Rescalvo FJ, Suarez E, Valverde-Palacios I, Santiago-Zaragoza JM, Gallego A (2018) Health monitoring of timber beams retrofitted with carbon fiber composites via the acoustic emission technique. Compos Struct 206:392–402. https://doi.org/10.1016/j.compstruct.2018.08.068

    Article  Google Scholar 

  247. Gomes GF, Mendéz YAD, P da Silva Lopes Alexandrino YAD, da Cunha SS, Ancelotti AC (2018) The use of intelligent computational tools for damage detection and identification with an emphasis on composites—a review. Compos Struct 196:44–54. https://doi.org/10.1016/j.compstruct.2018.05.002

  248. Adewuyi AP, Wu Z, Serker NHMK (2009) Assessment of vibration-based damage identification methods using displacement and distributed strain measurements. Struct Heal Monit 8:443–461. https://doi.org/10.1177/1475921709340964

    Article  Google Scholar 

  249. Katsikeros CE, Labeas GN (2009) Development and validation of a strain-based structural health monitoring system. Mech Syst Signal Process 23:372–383. https://doi.org/10.1016/j.ymssp.2008.03.006

    Article  Google Scholar 

  250. Kim D-H, Lee K-H, Ahn B-J, Lee J-H, Cheong S-K, Choi I-H (2013) Strain and damage monitoring in solar-powered aircraft composite wing using fiber Bragg grating sensors. In: Lynch JP, Yun C-B, Wang K-W (eds) Proceedings of the SPIE 8692, sensors smart structures. Technolohy Civil and Mechanical Aerospace Systems. 2013, SPIE, San Diego, CA. pp 576–581. https://doi.org/10.1117/12.2009232

  251. Qiu L, Fang F, Yuan S, Boller C, Ren Y (2019) An enhanced dynamic Gaussian mixture model-based damage monitoring method of aircraft structures under environmental and operational conditions. Struct Heal Monit 18:524–545. https://doi.org/10.1177/1475921718759344

    Article  Google Scholar 

  252. Alvarez-Montoya J, Carvajal-Castrillón A, Sierra-Pérez J (2020) In-flight and wireless damage detection in a UAV composite wing using fiber optic sensors and strain field pattern recognition. Mech Syst Signal Process 136:106526. https://doi.org/10.1016/j.ymssp.2019.106526

    Article  Google Scholar 

  253. Wang Y, Qiu L, Luo Y, Ding R, Jiang F (2020) A piezoelectric sensor network with shared signal transmission wires for structural health monitoring of aircraft smart skin. Mech Syst Signal Process 141:106730. https://doi.org/10.1016/j.ymssp.2020.106730

    Article  Google Scholar 

  254. Bergmayr T, Winklberger M, Kralovec C, Schagerl M (2020) Strain measurements along zero-strain trajectories as possible structural health monitoring method for debonding initiation and propagation in aircraft sandwich structures. Procedia Struct Integr 28:1473–1480. https://doi.org/10.1016/j.prostr.2020.10.121

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University Institute of Engineering and Technology, Panjab University, Chandigarh, 160014, India

    Tarunpreet Singh & Shankar Sehgal

Authors
  1. Tarunpreet Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shankar Sehgal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shankar Sehgal.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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

Singh, T., Sehgal, S. Structural Health Monitoring of Composite Materials. Arch Computat Methods Eng 29, 1997–2017 (2022). https://doi.org/10.1007/s11831-021-09666-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11831-021-09666-8

Search

Navigation