Damage Monitoring of Regularly Arrayed Short-Fiber-Reinforced Composite Laminates under Tensile Load Based on Acoustic Emission Technology

Author:

Cai Hongda1,Lu Wenlong2,Ma Jingxuan1,Huang Yinyuan13,Hu Junfeng14ORCID

Affiliation:

1. School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211800, China

2. School of Energy Science and Engineering, Nanjing Tech University, Nanjing 211800, China

3. Suzhou Yihe Yongli New Energy Co., Ltd., Suzhou 215400, China

4. Jiangsu Olymspan Thermal Energy Equipment Co., Ltd., Changzhou 213101, China

Abstract

Carbon-fiber-reinforced polymer (CFRP) composites are widely used in lightweight structures because of their high specific strength, specific modulus, and low coefficient of thermal expansion. Additionally, the unidirectionally arrayed chopped strand (UACS) laminates have excellent mechanical properties and flowability, making them suitable for fabricating structures with complex geometry. In this paper, the damage process of UACS quasi-isotropic laminates under tensile load was tested using acoustic emission detection technology. The mechanical properties and damage failure mechanism of UACS laminates were studied combined with finite element calculation. By comparing and analyzing the characteristic parameters of acoustic emission signals such as amplitude, relative energy, and impact event, it is found that acoustic emission behavior can accurately describe the damage evolution of specimens during loading. The results show that the high-amplitude signals representing fiber fracture in continuous fiber laminates are concentrated in the last 41%, while in UACS laminates they are concentrated in the last 30%. In UACS laminates, more of the damage is caused by matrix cracks and delamination with medium- and low-amplitude signals, which indicates that UACS laminates have a good suppression effect on damage propagation. The stress–strain curves obtained from finite element analysis agree well with the experiment results, showing the same damage sequence, which confirms that the model described in this research is reliable.

Funder

Postgraduate Research & Practice Innovation Program of Jiangsu Province

National Undergraduate Innovation and Entrepreneurship Training Program

National Natural Science Foundation of China

Publisher

MDPI AG

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