Acoustic Emission Based on Cluster and Sentry Function to Monitor Tensile Progressive Damage of Carbon Fiber Woven Composites

Wei Zhou,Peng-Fei Zhang,Yan-Nan Zhang

doi:10.3390/app8112265

Abstract

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.

Highlights

Carbon fiber woven composites have been used in a wide range of applications in, for example, aerospace, automobile, and industry due to their high specific strength and stiffness and other outstanding properties [1,2,3,4]
Several methods like high-pass filters and linear source location filters have been proposed to remove the noise and acquire the accurate selection of acoustic emission (AE) signals originating from the damage [36,37,38]
In order to ensure that most AE signals were generated in the gauge section, the AE signals were monitored with two identical sensors located 55 mm apart

Summary

Introduction

Carbon fiber woven composites have been used in a wide range of applications in, for example, aerospace, automobile, and industry due to their high specific strength and stiffness and other outstanding properties [1,2,3,4]. In spite of these advantages, damages such as matrix cracking and debonding that appear during the manufacturing and service processes are still unavoidable. Characterization and process monitoring of the damage evolution of the composites is highly necessary [5,6,7,8,9]. Acoustic emission (AE) technology can provide real-time information varying with external variables such as load, time, and temperature. It has been used more and more widely in online monitoring and the early prediction of damage [13,14,15]

Methods

Results

Conclusion