Wavelet-based acoustic emission characterization of damage mechanism in composite materials under mode I delamination at different interfaces

Abstract

Abstract. In this paper, acoustic emission (AE) monitoring with a wavelet-based signal processing technique is developed to detect the damage types during mode I delamination on glass/polyester composite materials. Two types of specimen at different midplane layups, woven/woven (T3) and unidirectional/unidirectional (T5), leading to different levels of damage evolution, were studied. Double cantilever beam (DCB) is applied to simulate delamination process for all specimens. Firstly, the obtained AE signals are decomposed into various wavelet levels. Each level includes detail and approximation that are called components and related to a specific frequency range. Secondly, the energy distribution criterion is applied to find the more significant components each one of which is in relation to a distinct type of damage. The results show that the energy of AE signals has been concentrated in three significant components for both of the specimens. There is a difference in energy distribution of similar components of two specimens. It indicates that there is a dissimilar dominant damage mechanism for two different interfaces during the delamination process. Additionally, the microscopic observation (SEM) is used to determine how the different fracture mechanisms are related to the dominant corresponding wavelet components.

Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm

“…Wavelet transform has been used by several researchers in studying the relationship between AE signals and damage modes. [19][20][21] The results of these studies indicate that frequency analysis is an effective way for processing AE signals of composite materials.…”

Damage Classification of Sandwich Composites Using Acoustic Emission Technique and k-means Genetic Algorithm

“…Some advantages of AE method are online failure inspection, recognition and classification of damage mechanisms in real time [3][4][5][6][7][8]. Acoustic Emission (AE) is a robust nondestructive method for detection and recognition of different damage modes in composite materials.…”

An Investigation of Acoustic Emission Signal Attenuation for Monitoring of Progressive Failure in Fiberglass Reinforced Composite Laminates

“…For this particular purpose, continuous wavelet transform (CWT) provides better accuracy for both time and frequency information compared with the short-time Fourier transform (STFT) method (Daubechies, 1990). Several researchers interested in MAE have successfully used wavelet analysis, either for source location (Jiao et al, 2004;Jiao et al, 2006;Jiao et al, 2008;Oskouei et al, 2009;Hamstad et al, 2002) or for failure characterization (Ni & Iwamoto, 2002;Marec et al, 2008). However, Hafizi et al (2012) have shown the suitability of source mapping using STFT in their work.…”