Semantic segmentation of progressive micro-cracking in polymer composites using Attention U-Net architecture

Valeri Ivanov Petkov, Vivek Richards Pakkam Gabriel, Patrik Fernberg
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Abstract

The present study delivers a methodology for investigating the gradual damage development in a carbon fibre-reinforced cross-ply polymer composite during a sequence of thermo-mechanical loadings with the help of X-ray computed tomography. The procedure allows an in-depth analysis of the occurrence and nature of the multiple cracks that form within layers oriented perpendicular, or transverse, to the loading direction. This is achieved by using Attention U-Net architecture for semantic segmentation of the transverse cracks. The model shows promising results, through an ability to identify all the transverse cracks and reflect the damage progression. The described method provides a robust routine for analysing challenging polymer composite tomographic datasets.

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利用注意力 U-Net 架构对聚合物复合材料中的渐进式微裂纹进行语义分割
本研究提供了一种方法,利用 X 射线计算机断层扫描技术研究碳纤维增强交叉层聚合物复合材料在一系列热机械加载过程中的渐进损伤发展。该程序可以深入分析垂直于或横向于加载方向的层内形成的多裂纹的发生和性质。这是通过使用 Attention U-Net 架构对横向裂缝进行语义分割来实现的。该模型能够识别所有横向裂缝,并反映出损坏的发展过程,显示出良好的效果。所描述的方法为分析具有挑战性的聚合物复合层析成像数据集提供了一种可靠的方法。
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