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

Abstract

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.

Damage evaluation of laminated composites under low-velocity impact tests using acoustic emission method

“…Accordingly, three different mechanisms are considered for UD samples. According to previous works, 17,18 in order to classify these damage mechanisms, their AE characteristics were extracted applying a similar procedure. Frequency content for each AE event was analyzed using Hilbert transform (HT) technique.…”

“…Several damage mechanisms, such as matrix cracking, fiber breakage, matrix/fiber debonding and delamination, can be created when a composite laminate is subjected to the low velocity impact. In this case, acoustic emission (AE), as a non-destructive approach, has the ability to characterize these failure modes [16][17][18] for in-service monitoring conditions. Some studies [19][20][21] utilized rough AE descriptors such as frequency, amplitude, and energy of AE signals to characterize different failure mechanisms in composite laminates.…”

Study on tensile properties of carbon fiber/epoxy laminated woven composites with ply splicing

“…There will be AE signals with different characteristics corresponding to different damage modes of specimens during loading including matrix cracking, fiber/matrix debonding and fiber breakage. 22,23 At present, the mainstream method of pattern recognition is the clustering method based on multi-parameter analysis. 21,24,25 Cluster analysis based on time and frequency characteristics shows that peak frequencies of AE signals can represent specific damage mechanisms.…”

Acoustic Emission Characterization of Natural Fiber Reinforced Plastic Composite Machining Using a Random Forest Machine Learning Model

“…Relative to connecting the AE responses to various failure modes, earlier efforts [23,51,61] 11( f ), the random forest approach is capable of picking up most significant frequency features (within frequency ranges of 260 kHz-280 Hz and 220-240 kHz) to achieve a classification accuracy around 95.3%. Table 5 suggests that these frequency features determining the classification accuracy for FOA = 45 deg versus 90 deg are related to fiber-matrix debonding and fiber pull-out [23], which are fundamental cutting mechanisms that distinguish the machining processes between FOA = 45 deg and 90 deg [53].…”