On the identification of the failure mechanisms in oxide/oxide composites using acoustic emission

Kostopoulos, V.; Λούτας, Θεόδωρος; Kontsos, Antonios; Sotiriadis, G.; Pappas, Y.Z.

doi:10.1016/s0963-8695(03)00068-9

Cited by 93 publications

(57 citation statements)

References 8 publications

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“…In this type of studies, a main assumption is done: signals are affected by propagation but they remain images of sources. Therefore, acoustic emission events can be classified using multivariable statistical analysis techniques and then attributed to a damage mechanism in the material [5][6][7][8][9][10][11][12]. The main assumption is: the acoustic signatures are unchanged during propagation and damage evolution.…”

Section: Introductionmentioning

confidence: 99%

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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%

“…For the unsupervised pattern recognition, the descriptors should be relevant and limited in number. The possibility to identify AE signatures of damage mechanisms is an established field [5][6][7][8][9][10][11][12]. In most studies, the attribution of system.…”

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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“…Many works [11][12][13][14][15][16] have shown that AE techniques and multivariable classification techniques are the basis of pattern recognition tools. Kostopoulos [12], Godin [13,14], Moevus [15,16] have identified different classes of AE signals which were attributed to damage modes in oxide/oxide, glass/polyester and SiCf/[Si-B-C] composites. Moevus [16] analyzed the AE data using an unsupervised multi-variable clustering technique.…”

Section: Introductionmentioning

confidence: 99%

Identification of a Critical Time with Acoustic Emission Monitoring during Static Fatigue Tests on Ceramic Matrix Composites: Towards Lifetime Prediction

et al. 2016

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Non-oxide fiber-reinforced ceramic-matrix composites are promising candidates for some aeronautic applications that require good thermomechanical behavior over long periods of time. This study focuses on the behavior of a SiC f /[Si-B-C] composite with a self-healing matrix at intermediate temperature under air. Static fatigue experiments were performed below 600 ¥ C and a lifetime diagram is presented. Damage is monitored both by strain measurement and acoustic emission during the static fatigue experiments. Two methods of real-time analysis of associated energy release have been developed. They allow for the identification of a characteristic time that was found to be close to 55% of the measured rupture time. This critical time reflects a critical local energy release assessed by the applicability of the Benioff law. This critical aspect is linked to a damage phase where slow crack growth in fibers is prevailing leading to ultimate fracture of the composite.

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“…A complete overview of damage recognition using AE is provided in ref [4], in most cases a complementary method is needed for distinguishing damage progression [5][6][7]. In some studies, unsupervised pattern recognition has implemented to cluster distinct type of damages [8][9][10]. Huguet et al [11] characterized AE signals using this technique with neural network linked with K-means algorithm.…”

Section: Introductionmentioning

confidence: 99%

Damage evaluation of composite materials using acoustic emission features and Hilbert transform

Shahri

Yousefi

Fotouhi

et al. 2015

Journal of Composite Materials

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One of the intricate issues of using acoustic emissions (AEs) for mechanical diagnostics in composite materials is establishing a relation between acoustic features and fracture behaviors. Therefore Hilbert Transform (HT) which is a new method to investigate fracture and damage evolution were used to analyze AE features of cross ply polymer composite material subjected to ENF test which simulate mode II delamination. Two different mid-plane interface layups are used. HT is used to extract frequency range of each damages occurring in different stages of loading process for each layup. Phase angle of HT is used as a novel feature to distinguish frequency ranges of AE waveforms and the resulting ranges are correlated to the damage mechanisms of the material under investigation. Three important stages in mode II delamination, i.e. initiation, maximum load nearby and the region where crack reaches to the middle of the specimens, are investigated using the introduced method and the details of damages in those regions are characterized. The results of Hilbert transform was in good agreement with scanning electron microscope (SEM) pictures. As a result, it is shown that AE method accompanied with the presented method is a new appropriate approach to examine damage mechanisms in composite materials.

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On the identification of the failure mechanisms in oxide/oxide composites using acoustic emission

Cited by 93 publications

References 8 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

Identification of a Critical Time with Acoustic Emission Monitoring during Static Fatigue Tests on Ceramic Matrix Composites: Towards Lifetime Prediction

Damage evaluation of composite materials using acoustic emission features and Hilbert transform

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