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碳纤维-环氧树脂基复合材料层压板中横向开裂引发的声发射

Transverse Cracking Induced Acoustic Emission in Carbon Fiber-Epoxy Matrix Composite Laminates.

作者信息

Hamam Zeina, Godin Nathalie, Reynaud Pascal, Fusco Claudio, Carrère Nicolas, Doitrand Aurélien

机构信息

Univ Lyon, INSA-Lyon, UCBL, CNRS UMR5510, MATEIS, F-69621 Villeurbanne, France.

IRDL, CNRS UMR6027, F-29200 Brest, France.

出版信息

Materials (Basel). 2022 Jan 5;15(1):394. doi: 10.3390/ma15010394.

DOI:10.3390/ma15010394
PMID:35009539
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8746499/
Abstract

Transverse cracking induced acoustic emission in carbon fiber/epoxy matrix composite laminates is studied both experimentally and numerically. The influence of the type of sensor, specimen thickness and ply stacking sequence is investigated. The frequency content corresponding to the same damage mechanism differs significantly depending on the sensor and the stacking sequence. However, the frequency centroid does not wholly depend on the ply thickness except for the inner ply crack and a sensor located close enough to the crack. Outer ply cracking exhibits signals with a low-frequency content, not depending much on the ply thickness, contrary to inner ply cracking, for which the frequency content is higher and more dependent on the ply thickness. Frequency peaks and frequency centroids obtained experimentally are well captured by numerical simulations of the transverse cracking induced acoustic emission for different ply thicknesses.

摘要

对碳纤维/环氧树脂基复合材料层压板中横向裂纹引发的声发射进行了实验和数值研究。研究了传感器类型、试样厚度和铺层顺序的影响。对应于相同损伤机制的频率成分因传感器和铺层顺序的不同而有显著差异。然而，除了内层裂纹和距离裂纹足够近的传感器外，频率质心并不完全取决于层厚。外层裂纹产生的信号具有低频成分，与内层裂纹相反，外层裂纹信号对层厚的依赖性不大，内层裂纹的频率成分较高且更依赖于层厚。通过对不同层厚横向裂纹引发的声发射进行数值模拟，很好地捕捉到了实验获得的频率峰值和频率质心。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/8f0d35704363/materials-15-00394-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/8f0d35704363/materials-15-00394-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/668a2e922e57/materials-15-00394-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/521b813a2e48/materials-15-00394-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/4372b80a60ec/materials-15-00394-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/3c0847d8ae77/materials-15-00394-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/5a78c2340762/materials-15-00394-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/7032eba861e8/materials-15-00394-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/6652ae87f7c4/materials-15-00394-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/7d0803f26073/materials-15-00394-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cad/8746499/8f0d35704363/materials-15-00394-g012.jpg

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基于声发射信号、深度特征提取和机器学习的生物复合材料和玻璃纤维增强环氧树脂基复合材料的特性研究。
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