Data Merging of AE Sensors with Different Frequency Resolution for the Detection and Identification of Damage in Oxide-Based Ceramic Matrix Composites

Guel, Nicolas; Hamam, Zeina; Godin, Nathalie; Reynaud, Pascal; Caty, Olivier; Bouillon, Florent; Paillassa, Aude

doi:10.3390/ma13204691

Cited by 26 publications

(14 citation statements)

References 39 publications

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“…Indeed, few AE signal labels are confirmed by direct observations of the sources due to the difficulty of experimentally controlling the sources. Nevertheless, the possibility of identifying AE signatures of damage mechanisms is an established field [10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Acoustic Emission Signal Due to Fiber Break and Fiber Matrix Debonding in Model Composite: A Computational Study

et al. 2021

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Acoustic emission monitoring is a useful technique to deal with detection and identification of damage in composite materials. Over the last few years, identification of damage through intelligent signal processing was particularly emphasized. Data-driven models are developed to predict the remaining useful lifetime. Finite elements modeling (FEM) was used to simulate AE signals due to fiber break and fiber/matrix debonding in a model carbon fiber composite and thereby better understand the AE signals and physical phenomena. This paper presents a computational analysis of AE waveforms resulting from fiber break and fiber/matrix debonding. The objective of this research was to compare the AE signals from a validated fiber break simulation to the AE signals obtained from fiber/matrix debonding and fiber break obtained in several media and to discuss the capability to detect and identify each source.

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Section: Introductionmentioning

confidence: 99%

Acoustic Emission Signal Due to Fiber Break and Fiber Matrix Debonding in Model Composite: A Computational Study

et al. 2021

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“…Recently, Guel et al [9] used a multiparameter approach by integrating the acoustic results recorded from two different types of piezoelectric sensors. The parameters they used for this analysis were centroid frequency, peak frequency, and energy.…”

Section: Introductionmentioning

confidence: 99%

“…The parameters they used for this analysis were centroid frequency, peak frequency, and energy. Although these parameters have been commonly used by several researchers in the past, Guel et al used an exploratory data analysis for selecting these parameters [9]. Nonetheless, the parameters they used for analysis are quite common in the literature.…”

Section: Introductionmentioning

confidence: 99%

Multiparameter Approach for Damage Propagation Analysis in Fiber-Reinforced Polymer Composites

et al. 2021

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Assessing the damage evolution in carbon-fiber-reinforced polymer (CFRP) composites is an intricate task due to their complex mechanical responses. The acoustic emission technique (AE) is a non-destructive evaluation tool that is based on the recording of sound waves generated inside the material as a consequence of the presence of active defects. Proper analysis of the recorded waves can be used for monitoring the damage evolution in many materials, including composites. The acoustic track associated with the entire loading history of the sample or the structures is usually followed by using some descriptors, such as the amplitude of the sound waves and the number of counts. In this study, the acoustic emission in CFRP single-lap shear joints was monitored by using a multiparameter approach based on the contemporary analysis of multiple features, such as the absolute signal level (ASL), initiation frequency, and reverberation frequency, to understand whether a proper combination of them can be adopted for a more robust description of the damage propagation in CFRP structures. For selecting the best features, principal component analysis (PCA) was used. The selected features were classified into different clusters using fuzzy c-means (FCM) data clustering for analyzing the damage modes.

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“…Recently, Guel et al [9] used a multiparameter approach by integrating the acoustic results recorded from two different types of piezoelectric sensors. The parameters they used for this analysis are centroid frequency, peak frequency and energy.…”

Section: Introductionmentioning

confidence: 99%

“…The parameters they used for this analysis are centroid frequency, peak frequency and energy. Although these parameters have been commonly used by several researchers in the past, Guel et al used an exploratory data analysis for selecting these parameters [9]. Nonetheless, the parameters they have used for analysis are quite common in literature.…”

Section: Introductionmentioning

confidence: 99%

Multi-parameters approach for damage propagation analysis in Fiber Reinforced Polymer Composites

Pappalettera

Barile

Casavola

et al. 2020

Proceedings of 1st International Electronic Conference on Applied Sciences

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Assessing damage evolution in Carbon Fiber Reinforced Polymer (CFRP) composites is an intricate task due to the complex mechanical response of the composites. The acoustic emission technique (AE) is a non-destructive technique based on the recording of sound waves generated inside the material as a consequence of the presence of active defects. Proper analysis of the recorded waves can be used for monitoring damage evolution in many materials including composites. The acoustic track associated with the entire loading history of the sample or the structures is usually followed by using some descriptors such as the amplitude of the sound waves, the number of counts and so on. In this paper the acoustic emission in CFRP single lap shear joints will be monitored by using a multiparameter approach based on the contemporary analysis of multiple features such as ASL, Initiation Frequency, Reverberation Frequency and so on to understand if a proper combination of them can be adopted for a more robust description of damage propagation in CFRP structures. For selecting the best features, Principal Component Analysis (PCA) is used. The selected features are classified into different clusters using Fuzzy c-means (FCM) data clustering for analyzing the damage modes.

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Data Merging of AE Sensors with Different Frequency Resolution for the Detection and Identification of Damage in Oxide-Based Ceramic Matrix Composites

Cited by 26 publications

References 39 publications

Acoustic Emission Signal Due to Fiber Break and Fiber Matrix Debonding in Model Composite: A Computational Study

Acoustic Emission Signal Due to Fiber Break and Fiber Matrix Debonding in Model Composite: A Computational Study

Multiparameter Approach for Damage Propagation Analysis in Fiber-Reinforced Polymer Composites

Multi-parameters approach for damage propagation analysis in Fiber Reinforced Polymer Composites

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