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Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection

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Bibliographic Details
Main Authors: Kailun, Deng, Haochen, Liu, Lichao, Yang
Format: Book
Language:English
Published: Springer 2023
Subjects:
CFRP
AI
Online Access:https://link.springer.com/article/10.1007/s00521-023-08293-7
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8295
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spelling oai:localhost:PNK-82952023-04-25T07:56:59Z Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection Kailun, Deng Haochen, Liu Lichao, Yang CFRP AI CC BY With the increasingly comprehensive utilisation of Carbon Fibre-Reinforced Polymers (CFRP) in modern industry, defects detection and characterisation of these materials have become very important and draw significant research attention. During the past 10 years, Artificial Intelligence (AI) technologies have been attractive in this area due to their outstanding ability in complex data analysis tasks. Most current AI-based studies on damage characterisation in this field focus on damage segmentation and depth measurement, which also faces the bottleneck of lacking adequate experimental data for model training. This paper proposes a new framework to understand the relationship between Barely Visible Impact Damage features occurring in typical CFRP laminates to their corresponding controlled drop-test impact energy using a Deep Learning approach. A parametric study consisting of one hundred CFRP laminates with known material specification and identical geometric dimensions were subjected to drop-impact tests using five different impact energy levels. 2023-04-25T07:56:59Z 2023-04-25T07:56:59Z 2023 Book https://link.springer.com/article/10.1007/s00521-023-08293-7 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8295 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic CFRP
AI
spellingShingle CFRP
AI
Kailun, Deng
Haochen, Liu
Lichao, Yang
Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
description CC BY
format Book
author Kailun, Deng
Haochen, Liu
Lichao, Yang
author_facet Kailun, Deng
Haochen, Liu
Lichao, Yang
author_sort Kailun, Deng
title Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
title_short Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
title_full Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
title_fullStr Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
title_full_unstemmed Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
title_sort classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00521-023-08293-7
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8295
_version_ 1764177438951079936
score 8.891053

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