Understanding the damage and failure of carbon/glass epoxy hybrid woven composites under tensile loading based on acoustic emission signals is a challenging task in their practical uses. In this study, an approach based on fuzzy c-means algorithm is proposed to process the acoustic emission signals from tensile loading of composites monitored by combining acoustic emission technology and digital image correlation method. The results show that the acoustic emission signals from tensile loading can be divided into three clusters. The three clusters correspond to three kinds of damage modes including matrix cracking, fiber/matrix debonding, delamination, and fiber breakage. By comparing the acoustic characteristics of these classes, a correlation procedure between the clusters and the damage mechanisms observed is proposed. Meanwhile, it can be found that debonding and fiber break signals for glass fiber correspond to a lower frequency range than that for carbon fiber. Moreover, the method combining acoustic emission and digital image correlation can effectively monitor the damage process of the specimen both on the inside and outside, which can provide a reference for the health monitoring of composite structure.

Understanding the tensile failure mechanisms in carbon fiber woven composites based on the acoustic emission (AE) technique is a challenging task. In this study, the mechanical behaviors of composites were studied under uniaxial tensile loading. Meanwhile, the internal damage evolution process in composites was monitored by AE and the recorded AE signals were analyzed. To achieve the dominant damage mechanisms in composites, five AE parameters such as rise time, duration, energy, peak amplitude, and frequency were selected for cluster analysis by a k-means algorithm. The results show that AE signals can be divided into three clusters based on microscopic observations and frequency range. The three clusters correspond to three kinds of damage modes such as matrix cracking, fiber/matrix debonding, and fiber breakage. In addition, the sentry function (SF) was adopted to investigate AE signals originated from the internal damage evolution in composites. It was found that the drop in the SF curve corresponds to the serious damage of the composites.