Damage characterization of laminated composites using acoustic emission: A review

Saeedifar, Milad

doi:10.1016/j.compositesb.2020.108039

Cited by 264 publications

(163 citation statements)

References 123 publications

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“…Nonetheless, several review works, which summarizes the importance and applications of different AE descriptors can be found in literatures. Particularly, Saeedifar and Zarouchas [16] have summarized the number of papers published each year, from 1975 onwards, on the damage assessment of laminated composites using the AE technique. In their research work, the damage initiation detection, damage identification and localization using AE technique by several research works has been summarized.…”

Section: Research Significancementioning

confidence: 99%

Damage Propagation Analysis in the Single Lap Shear and Single Lap Shear-Riveted CFRP Joints by Acoustic Emission and Pattern Recognition Approach

et al. 2020

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An innovative way of using the Acoustic Emission (AE) technique is introduced in this research work. The ratio of recorded acoustic energy and the counts recorded for each acoustic event were used for characterizing Carbon Fiber Reinforced Plastic (CFRP) laminates adhesively bonded with and without mechanical fasteners. The cumulative counts and cumulative energy of the recorded acoustic events were used for identifying the critical points of failure under loading of these hybrid joint specimens. The peak amplitude distribution was used for identifying the different damage modes such as delamination, matrix cracking and fiber breakage, albeit, ineffectively. The new parameter energy per count was introduced in this work, which can successfully identify the different damage modes under loading. To differentiate the damage modes using the energy per count, they were clustered using k-means++ pattern recognition technique. The method introduced in this work can estimate the damage modes of the CFRP specimens.

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Section: Research Significancementioning

confidence: 99%

Damage Propagation Analysis in the Single Lap Shear and Single Lap Shear-Riveted CFRP Joints by Acoustic Emission and Pattern Recognition Approach

et al. 2020

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“…One of the main reasons for its application is the fact that the AE is a passive technique, which means that the source of the acoustic signal is located inside the material, enabling the material's behavior monitoring under loading conditions [15]. The source of the AE signals can be related to damage nucleation and propagation, plastic deformation, or even internal friction [19]. The development of these damage mechanisms inside the material causes sudden internal displacements combined with spatial crack surface oscillations originating acoustic waves.…”

Section: The Use Of Acoustic Emission (Ae) Technique To Quantify Physmentioning

confidence: 99%

“…Some AE parameters, such as the peak amplitude, peak frequency, energy, duration, counts, and rise time, have been used to interpret acoustic signals and study the damage formation process in FRPs. Most of the works have focused on damage onset detection, damage location, damage identification, and studies related to the remaining useful life and residual strength of composite structures [19]. Barile et al used the sentry function to relate the acoustic energy with the strain energy released by the material during delamination propagation in [15] and investigated the effect of the number of plies, fiber orientation, and thickness of carbon fiber reinforced polymer (CFRP) composites on the AE parameters in [21].…”

Section: The Use Of Acoustic Emission (Ae) Technique To Quantify Physmentioning

confidence: 99%

Scrutinizing interlaminar fatigue loading cycle in composites using acoustic emission technique: Stress ratio influence on damage formation

Motta

Alderliesten

Shiino

et al. 2020

Composites Part A: Applied Science and Manufacturing

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Current models for delamination propagation prediction in fiber-reinforced polymer (FRP) composites exhibit limitations to explain the physics underlying the mechanisms of damage formation in fatigue. In order to contribute in this field, this research focuses on the study of damage development within a single loading cycle of FRP double cantilever beam specimens under different stress ratios (R). The acoustic emission technique was used to investigate damage propagation. Results showed that under high R-ratios, the load cycle spends an increased time above the threshold energy (U th ). This time difference affects the damage distribution within a single loading cycle. Furthermore, the steady-state delamination propagation was influenced by the R-ratio variation due to the modification of the external work applied to the specimen.

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“…The average duration of AE data collection is equal to the duration of stress-strain data collection as mentioned in Section 27. Each waveform consists of 1024 data samples (sampling rate 488 μs) and different AE features as highlighted in Fig 3. We consider average absolute energy (Abs energy) in this work which was mostly utilized in the literature [20] to characterize damage and failure phases of various types of composite materials. The average Abs energy was computed from each waveform energy feature.…”

Section: Damage and Failure Regions Characterization Of Carbon Fiber mentioning

confidence: 99%

Unsupervised bivariate data clustering for damage assessment of carbon fiber composite laminates

et al. 2020

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Damage assessment is a key element in structural health monitoring of various industrial applications to understand well and predict the response of the material. The big uncertainty in carbon fiber composite materials response is because of variability in the initiation and propagation of damage. Developing advanced tools to design with composite materials, methods for characterizing several damage modes during operation are required. While there is a significant amount of work on the analysis of acoustic emission (AE) from different composite materials and many loading cases, this research focuses on applying an unsupervised clustering method for separating AE data into several groups with distinct evolution. In this paper, we develop an adaptive sampling and unsupervised bivariate data clustering techniques to characterize the several damage initiations of a composite structure in different lay-ups. An adaptive sampling technique pre-processes the AE features and eliminates redundant AE data samples. The reduction of unnecessary AE data depends on the requirements of the proposed bivariate data clustering technique. The bivariate data clustering technique groups the AE data (dependent variable) with respect to the mechanical data (independent variable) to assess the damage of the composite structure. Tensile experiments on carbon fiber reinforced composite laminates (CFRP) in different orientations are carried out to collect mechanical and AE data and demonstrate the damage modes. Based on the mechanical stress-strain data, the results show the dominant damage regions in different lay-ups of specimens and the definition of the different states of damage. In addition, the states of the damage are observed using Scanning Electron Microscope (SEM) analysis. Based on the AE data, the results show that the strong linear correlation between AE and mechanical energy, and the classification of various modes of damage in all lay-ups of specimens forming clusters of AE energy with respect to the mechanical energy. Furthermore, the validation of the cluster-based characterization and improvement of the sensitivity of the damage modes classification are observed by the combined knowledge of AE and mechanical energy and time-frequency spectrum analysis.

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Damage characterization of laminated composites using acoustic emission: A review

Cited by 264 publications

References 123 publications

Damage Propagation Analysis in the Single Lap Shear and Single Lap Shear-Riveted CFRP Joints by Acoustic Emission and Pattern Recognition Approach

Damage Propagation Analysis in the Single Lap Shear and Single Lap Shear-Riveted CFRP Joints by Acoustic Emission and Pattern Recognition Approach

Scrutinizing interlaminar fatigue loading cycle in composites using acoustic emission technique: Stress ratio influence on damage formation

Unsupervised bivariate data clustering for damage assessment of carbon fiber composite laminates

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