Signal-based acoustic emission data are analysed in this research work for identifying the damage modes in carbon fibre–reinforced plastic (CFRP) composites. The research work is divided into three parts: analysis of the shifting in the spectral density of acoustic waveforms, use of waveform entropy for selecting the best wavelet and implementation of wavelet packet transform (WPT) for identifying the damage process. The first two methodologies introduced in this research work are novel. Shifting in the spectral density is introduced in analogous to ‘flicker noise’ which is popular in the field of waveform processing. The entropy-based wavelet selection is refined by using quadratic Renyi’s entropy and comparing the spectral energy of the dominating frequency band of the acoustic waveforms. Based on the method, ‘dmey’ wavelet is selected for analysing the waveforms using WPT. The slope values of the shifting in spectral density coincide with the results obtained from WPT in characterising the damage modes. The methodologies introduced in this research work are promising. They serve the purpose of identifying the damage process effectively in the CFRP composites.
HamstadMA. Thirty years of advances and some remaining challenges in the application of acoustic emission to composite materials. In: KishiTOhtsuMYuyamaS (eds) Acoustic emission–Beyond the millennium. Oxford: Elsevier, 2000, pp. 77–91.
2.
SauseMG. In situ monitoring of fiber-reinforced composites: theory, basic concepts, methods, and applications. Switzerland: Springer, 2016, Vol. 242.
3.
SaeedifarMZarouchasD. Damage characterization of laminated composites using acoustic emission: a review. Composites B: Eng2020; 195: 108039.
4.
BarileCCasavolaCPappaletteraG, et al.Application of different acoustic emission descriptors in damage assessment of fiber reinforced plastics: a comprehensive review. Eng Fracture Mech2020; 235: 107083.
5.
SauseMGRMüllerTHoroschenkoffA, et al.Quantification of failure mechanisms in mode-I loading of fiber reinforced plastics utilizing acoustic emission analysis. Compos Sci Technol2012; 72(2): 167–174.
6.
BarileCCasavolaCPappaletteraG, et al.Damage characterization in composite materials using acoustic emission signal-based and parameter-based data. Compos B: Eng2019; 178: 107469.
7.
BarileCCasavolaCPappaletteraG, et al.Experimental wavelet analysis of acoustic emission signal propagation in CFRP. Eng Fract Mech2019; 210: 400–407.
8.
MacDonaldDKC. Noise and fluctuations: an introduction. USA: Dover Publications, 2006.
9.
DuttaPHornPM. Low-frequency fluctuations in solids:1fnoise. Rev Mod Phys1981; 53(3): 497–516.
10.
ChandaranaNSanchezDSoutisC, et al.Early damage detection in composites during fabrication and mechanical testing. Materials2017; 10(7): 685.
11.
OzFEErsoyNLomovSV. Do high frequency acoustic emission events always represent fibre failure in CFRP laminates?Composites A: Appl Sci Manufac2017; 103: 230–235.
12.
HoogeFN. 1/ƒ noise is no surface effect. Phys Lett A1969; 29(3): 139–140.
13.
GildenDL. Cognitive emissions of 1/f noise. Psychol Rev2001; 108(1): 33–56.
14.
MilottiE. 1/f noise: a pedagogical review. 2002. arXiv preprint physics/0204033.
15.
De CoenselBBotteldoorenDDe MuerT. 1/f noise in rural and urban soundscapes. Acta acustica united with acustica2003; 89(2): 287–295.
16.
CarpinteriALacidognaGAccorneroF. Fluctuations of 1/f noise in damaging structures analyzed by acoustic emission. Appl Sci2018; 8(9): 1685.
17.
FriedrichLColpoAMaggiA, et al.Damage process in glass fiber reinforced polymer specimens using acoustic emission technique with low frequency acquisition. Compos Struct2021; 256: 113105.
18.
ShannonCE. A mathematical theory of communication. ACM SIGMOBILE mobile Comput Commun Rev2001; 5(1): 3–55.
MannRPGarnettR. The entropic basis of collective behaviour. J R Soc Interf2015; 12(106): 20150037.
21.
AmigóJBaloghSHernándezS. A brief review of generalized entropies. Entropy2018; 20(11): 813.
22.
PrincipeJCXuDFisherJ, et al.Information theoretic learning. In: HaykinS (ed) Unsupervised adaptive filtering. New York, USA: Wiley, 2000, pp. 265–319.
23.
TanvirFSattarTMbaD, et al.Identification of fatigue damage evaluation using entropy of acoustic emission waveform. SN Appl Sci2020; 2(1): 1–15.
24.
RenyiA. On measures of entropy and information. In: Proceedings of the fourth berkeley symposium on mathematical statistics and probability, volume 1: contributions to the theory of statistics, 1961, Berkeley, 20-30 June 1960. The Regents of the University of California.
25.
CornforthDJTarvainenMPJelinekHF. How to calculate Renyi entropy from heart rate variability, and why it matters for detecting cardiac autonomic neuropathy. Front Bioeng Biotechnol2014; 2: 34.
26.
ColesPJBertaMTomamichelM, et al.Entropic uncertainty relations and their applications. Rev Mod Phys2017; 89(1): 015002.
27.
HartleyRVL. Transmission of Information1. Bell Syst Tech J1928; 7(3): 535–563.
28.
ShannonCE. A mathematical theory of communication. Bell Syst Tech J1948; 27(3): 379–423.
29.
CsiszarI. Generalized cutoff rates and Renyi’s information measures. IEEE Trans Inf Theor1995; 41(1): 26–34.
30.
BennettCHBrassardGCrépeauC, et al.Generalized privacy amplification. IEEE Trans Inf Theor1995; 41(6): 1915–1923.
31.
ZhangXFengNWangY, et al.Acoustic emission detection of rail defect based on wavelet transform and Shannon entropy. J Sound Vibration2015; 339: 419–432.
32.
KankarPKSharmaSCHarshaSP. Fault diagnosis of ball bearings using continuous wavelet transform. Appl Soft Comput2011; 11(2): 2300–2312.
33.
MallatSG. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans pattern Anal mach intell1989; 11(7): 674–693.
WickerhauserMV. Adapted wavelet analysis: from theory to software. Boca Raton, FL, USA: CRC Press, 1996.
36.
SaeedifarMNajafabadiMAZarouchasD, et al.Barely visible impact damage assessment in laminated composites using acoustic emission. Composites B: Eng2018; 152: 180–192.
37.
HabibiMLaperrièreL. Digital image correlation and acoustic emission for damage analysis during tensile loading of open-hole flax laminates. Eng Fract Mech2020; 228: 106921.
38.
MohammadiRNajafabadiMASaghafiH, et al.The effect of mode II fatigue crack growth rate on the fractographic features of CFRP composite laminates: an acoustic emission and scanning electron microscopy analysis. Eng Fract Mech2021; 241: 107408.
39.
Ben AmeurMEl MahiARebiereJL, et al.Investigation and identification of damage mechanisms of unidirectional carbon/flax hybrid composites using acoustic emission. Eng Fract Mech2019; 216: 106511.
40.
MouzakisDEDimogianopoulosDG. Acoustic emission detection of damage induced by simulated environmental conditioning in carbon fiber reinforced composites. Eng Fracture Mech2019; 210: 422–428.
41.
NiQQJinenE. Fracture behavior and acoustic emission in bending tests on single-fiber composites. Eng Fract Mech1997; 56(6): 779–796.
42.
PappasYZKostopoulosV. Toughness characterization and acoustic emission monitoring of a 2-D carbon/carbon composite. Eng Fract Mech2001; 68(14): 1557–1573.
43.
BarileC. Innovative mechanical characterization of CFRP by using acoustic emission technique. Eng Fract Mech2019; 210: 414–421.
44.
ASTM International. ASTM D5528-13, Standard Test Method for Mode I Interlaminar Fracture Toughness of Unidirectional Fiber-Reinforced Polymer Matrix Composites, West Conshohocken, PA: ASTM International, 2013, Available atwww.astm.org.
45.
BarileCCasavolaCMoramarcoV, et al.Bonding characteristics of single- and joggled-lap CFRP specimens: mechanical and acoustic investigations. Appl Sci2020; 10(5): 1782.
46.
BarileCCasavolaCPappaletteraG, et al.Damage assessment of carbon fibre reinforced plastic using acoustic emission technique: experimental and numerical approach. Structural Health Monitoring, 2020; 20: 1090–1101.
47.
BarileCCasavolaCPappaletteraG, et al.Acoustic emission descriptors for the mechanical behavior of selective laser melted samples: an innovative approach. Mech Mater2020; 148: 103448.
