Failure Assessment and Evaluation of Damage Development and Crack Growth in Polymer Composites Via Localization of Acoustic Emission Events: A Review

Romhány, Gábor; Czigány, Tibor; Karger‐Kocsis, J.

doi:10.1080/15583724.2017.1309663

Cited by 72 publications

(47 citation statements)

References 106 publications

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“…It is used as a Non-Destructive Testing technique to monitor damage in composites materials and structures [1][2][3][4]. Usually, piezoelectric sensors applied directly on the samples surface capture these elastic waves.…”

Section: Introductionmentioning

confidence: 99%

Challenges and Limitations in the Identification of Acoustic Emission Signature of Damage Mechanisms in Composites Materials

2018

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Acoustic emission is a part of structural health monitoring (SHM) and prognostic health management (PHM). This approach is mainly based on the activity rate and acoustic emission (AE) features, which are sensitive to the severity of the damage mechanism. A major issue in the use of AE technique is to associate each AE signal with a specific damage mechanism. This approach often uses classification algorithms to gather signals into classes as a function of parameters values measured on the signals. Each class is then linked to a specific damage mechanism. Nevertheless, each recorded signal depends on the source mechanism features but the stress waves resulting from the microstructural changes depend on the propagation and acquisition (attenuation, damping, surface interactions, sensor characteristics and coupling). There is no universal classification between several damage mechanisms. The aim of this study is the assessment of the influence of the type of sensors and of the propagation distance on the waveforms parameters and on signals clustering.

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Section: Introductionmentioning

confidence: 99%

Challenges and Limitations in the Identification of Acoustic Emission Signature of Damage Mechanisms in Composites Materials

2018

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“…The AE monitoring is used in many areas of engineering and vast comprehensive reviews on its application can be found in literature, e.g. aerospace engineering applications (Holford et al 2017), testing of polymer composites (Romhány et al 2017), monitoring of concrete structures (Zaki et al 2015;Noorsuhada 2016) and hydraulic fracture propagation in rocks (Bunger et al 2015). Fig.…”

Section: Acoustic Emission Monitoringmentioning

confidence: 99%

Computational monitoring in real time: review of methods and applications

Dyskin

Başarır

Doherty

et al. 2018

Geomech. Geophys. Geo-energ. Geo-resour.

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Continuous monitoring of mechanical parameters determining the state of natural and manmade systems is essential in a wide range of engineering disciplines from mechanical to civil and geotechnical engineering. To be effective, the monitoring response time needs to be commensurate with the characteristic time of variation of the processes being monitored e.g. from seconds as for example in some machinery, to weeks and months for mining excavations and years in the case of structures. The methods of measurement can therefore differ significantly for different applications. In spite of this, the methods of information processing-the computational monitoring-have considerable commonality. This review focuses on the methods of computational monitoring in solid and structural mechanics problems in different engineering applications. The traditional methods of monitoring are reviewed along with the corresponding computational and measurement methods. The basic principles of the computational monitoring in real time are established.

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“…Similar parameters can be obtained from the mean spectra of a series of AE signals, and histograms and/or cross-plots can be calculated from the data of single AE signals. 2,4 Special techniques can provide information in both the time and the frequency domain, resulting in time-dependent spectrum statistics. 2,4 The classic method is the short time FFT (SFFT) technique, which uses a moving time window.…”

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confidence: 99%

“…2,4 Special techniques can provide information in both the time and the frequency domain, resulting in time-dependent spectrum statistics. 2,4 The classic method is the short time FFT (SFFT) technique, which uses a moving time window. In the case of wavelet transformations (WT), AE signals are analyzed with the help of various wavelet components.…”

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confidence: 99%

“…It can be performed by applying several sensors and making use of the difference between the detection times of single AE hits and the speed of sound in the material tested. 2,4 Hafizi et al 33 proposed a signal attenuation-based source mapping instead of sound velocity mapping. From these data, spatial histograms, the damage zone and its development or crack initiation and propagation can be determined and monitored.…”

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Novel evaluation method of acoustic emission data based on statistical fiber bundle cells

Vas

Kocsis²,

Czigány

et al. 2019

Journal of Composite Materials

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In general, the aim of acoustic emission (AE) assisted tensile tests of composite materials is to identify and characterize the damage and failure modes of the specimens. This paper presents a fiber-bundle-cells (FBC) based statistical model, which provides a possible solution to the problem of characterizing the mechanical and failure behavior of the material. The model, based on the results of mechanical tests and AE measurements, decomposes the measured AE event number and tensile force-load time processes into components corresponding to the different damage modes. The AE events belonging to different failure modes are described by inhomogeneous Poisson point processes, while failures are modeled with the breakage of fibers as elementary parts of the sample. Hence damage modes can be characterized with the number fraction, and the tensile strength and signal energy distributions of the components. Moreover, the variation of the number fraction of the intact or damaged fibers as a function of the load time can be calculated and depicted as well. As reliability function or a kind of damage map, it reveals the mechanical load-bearing ability of the material tested. The applicability of the model is demonstrated by compact tension testing and the comparison of short and long glass fiber reinforced VERTON PP sheets and injection molded wood fiber reinforced PP composites.With the help of fast Fourier transformation (FFT), the frequency components of the single AE signals can be characterized by the amplitude or power spectrum in the frequency domain. Their description parameters are the bandwidth (B), the mean frequency (fm), the frequency of the maximum amplitude component (fP), and the amplitude (AP) or energy (UP) of the maximum peak. Similar parameters can be obtained from the mean spectra of a series of AE signals, and histograms and/or cross-plots can be calculated from the data of single AE signals. 2,4 Special techniques can provide information in both the time and the frequency domain, resulting in time-dependent spectrum statistics. 2,4 The classic method is the short time FFT (SFFT) technique, which uses a moving time window. In the case of wavelet transformations (WT), AE signals are analyzed with the help of various wavelet components. The signal transformations mentioned above provide additional or in itself usable information about the sources and failure modes in the frequency domain [21][22][23][24][25][26] or both in the time and the frequency domains [27][28][29][30][31][32][33][34][35][36] . In the latter case, wavelet transformations based on Haar 28 or Gabor 27, 33 wavelet components as well as Hilbert-Huang transform 30 can be used to decompose the AE signals and calculate the energy of the components. [27][28][29][30][31][32][33][34][35][36] In the case of thin plates, modal analysis can be applied to study and separate extensional and flexural Lamb waves. 37,38 The finite element method (FEM) can give a good base for wave discrimination. 38 The localization of a single AE signal in the spe...

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Failure Assessment and Evaluation of Damage Development and Crack Growth in Polymer Composites Via Localization of Acoustic Emission Events: A Review

Cited by 72 publications

References 106 publications

Challenges and Limitations in the Identification of Acoustic Emission Signature of Damage Mechanisms in Composites Materials

Challenges and Limitations in the Identification of Acoustic Emission Signature of Damage Mechanisms in Composites Materials

Computational monitoring in real time: review of methods and applications

Novel evaluation method of acoustic emission data based on statistical fiber bundle cells

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