Identification of fatigue damage modes for carbon fiber/epoxy composites using acoustic emission monitoring under fully reversed loading

Abstract

In this study, the fatigue damage modes of carbon fiber/epoxy composite laminates with symmetrical architecture were investigated by acoustic emission (AE) technique under fully reversed loading. The principal component analysis and the K‐means cluster analysis using correlation AE characteristic parameters, including the energy, the amplitude, and the duration time, were performed to identify various damage modes during the fatigue test process. The analysis results of the AE signals indicated that the high‐intensity AE signals were generated by the compressive load and the low‐intensity AE signals were generated by the tensile load. The maximum energy and duration time generated by the compression load are approximately 20 and 10 times that of the tensile load, respectively, which was consistent with the force‐controlled static test results under tension and compression loadings. Therefore, the fatigue damage caused by the compressive load is much greater than that of tensile load under fully reversed loading. The results of the multi‐AE parametric clustering analysis combined with scanning electron microscope micromorphology revealed that the damage modes of the laminate specimens were classified into five types, namely matrix cracks, fiber/epoxy interface debonding, shear, delamination, and fiber breakage. In addition, the damage modes at different stages during the fatigue test process were also analyzed and discussed.

Identification of micro‐failure processes of HDPE‐henequen fiber composite material by using acoustic emission monitoring: Effect of fiber surface modification

“…Consequently, evaluate failure mechanisms by using fibers embedded on polymer matrix allows the understanding of fundamental mechanical behavior. [23][24][25][26][27][28][29] The applications of polymeric composites reinforced with natural short fibers have increased substantially; they form an essential part in the design process of some of its components in sectors such as the automotive, marine and aeronautical industries. When one of these materials is subjected to external loads, it is crucial to ensure efficient stress transfer in the fiber-matrix interface region; there are microcracks that are not perceptible by the human ear and eye, therefore it is important to investigate the origin and evolution of these microdamages, as well as the effect of the different surface treatments on the fibers in order to increase the material opposition to perceive damage to delay fracture.…”

Damage mode identification in carbon/epoxy composite via machine learning and acoustic emission

“…There is now broad consensus that peak frequency and amplitudes are widely applicable to distinguish different damage modes in composites. [25][26][27] It is also known from Figure 4 that peak frequency and amplitudes are not strongly correlated with other parameters, so they are extracted in advance as the characteristic parameters. Then, PCA was performed on other parameters in order to reduce the dimensionality of the data set and to improve the efficiency of the operation.…”

An Improved Identification Method of Pipeline Leak Using Acoustic Emission Signal

“…In the 1950s, the German researcher Kaiser [24] first discovered the phenomenon of acoustic emission in metal deformation and proposed the concepts of burst-type and continuous-type acoustic emission signals. Over more than half a century of development, both the technology and theory of acoustic emission have significantly improved and found extensive applications in various industries, such as civil engineering, petrochemicals, aerospace, and marine engineering [25][26][27][28][29][30][31], indicating a promising future. Meniconi, S et al [32,33] innovatively proposed a transient analysis method for fault diagnosis of underwater pipelines, which holds significant implications for the advancement of SHM techniques.…”