Investigation on damage behaviors of carbon fiber‐reinforced nylon 6 thermoplastic composite laminates using acoustic emission and digital image correlation techniques

IF 4.8 2区 材料科学 Q2 MATERIALS SCIENCE, COMPOSITES
Jixin Zhu, Kejun Hu, Wenqin Han, Qinghe Shi, Yingming Wang, Fengling Zhao, Fuxian Zhu
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Abstract

The objective of this paper is to analyze the mechanical properties and damage mechanisms of carbon fiber‐reinforced polyamide thermoplastic composite laminates. Four specimens with different ply orientations were designed for open‐hole tensile experiments, and interlaminar toughness experiments including double cantilever beam and end‐notched flexural were carried out. The experimental process was monitored synchronously using acoustic emission, and the strain field changes of the tensile specimens were captured using digital image correlation technology. The unsupervised clustering of the peak frequencies of the acoustic emission signals based on the K‐means++ algorithm was employed to ascertain the peak frequency ranges corresponding to the various damage modes. Typical signals from different specimens were selected, and the gray wolf algorithm was used to optimize the variational modal parameters to decompose the signals. The waveform characteristics, frequency components, and Hilbert spectra of each damage mode were given. The correlation analysis of the intrinsic mode function (IMF) components of the same damage in different specimens demonstrated that the IMF components exhibited high similarity. By analyzing the time series changes in the energy of each damage mode in different specimens, the contribution of different damage modes to the evolution of laminated plate damage was evaluated.Highlights The mechanical properties of CF/PA6 laminates were investigated based on open‐hole tensile specimens and pre‐cracked delamination specimens. Unsupervised clustering of AE peak frequencies using K‐means++ to establish the relationship between peak frequencies and damage patterns. AE counts and cumulative energy were used to assess damage evolution. By identifying a single damage signal and providing a more intuitive treatment of the damage energy evolution.

Abstract Image

利用声发射和数字图像相关技术研究碳纤维增强尼龙 6 热塑性复合材料层压板的损伤行为
本文旨在分析碳纤维增强聚酰胺热塑性复合材料层压板的力学性能和损伤机理。设计了四种不同层向的试样进行开孔拉伸实验,并进行了层间韧性实验,包括双悬臂梁和端面缺口弯曲实验。实验过程采用声发射进行同步监测,并利用数字图像相关技术捕捉拉伸试样的应变场变化。基于 K-means++ 算法对声发射信号的峰值频率进行无监督聚类,以确定各种损伤模式对应的峰值频率范围。选取不同试样的典型信号,利用灰狼算法优化变模态参数,对信号进行分解。给出了每种损伤模式的波形特征、频率成分和希尔伯特频谱。对不同试样中相同损伤的本征模态函数(IMF)分量进行的相关性分析表明,IMF 分量具有很高的相似性。通过分析不同试样中每种损伤模式能量的时间序列变化,评估了不同损伤模式对层压板损伤演变的贡献。 重点研究内容 基于开孔拉伸试样和预裂纹分层试样,研究了 CF/PA6 层压板的力学性能。使用 K-means++ 对 AE 峰值频率进行无监督聚类,以确定峰值频率与损伤模式之间的关系。AE 计数和累积能量用于评估损伤演变。通过识别单一损伤信号,对损伤能量演变进行更直观的处理。
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来源期刊
Polymer Composites
Polymer Composites 工程技术-材料科学:复合
CiteScore
7.50
自引率
32.70%
发文量
673
审稿时长
3.1 months
期刊介绍: Polymer Composites is the engineering and scientific journal serving the fields of reinforced plastics and polymer composites including research, production, processing, and applications. PC brings you the details of developments in this rapidly expanding area of technology long before they are commercial realities.
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