@inproceedings{4ba8ccc3fe7f42e4b59b573eae8045c5,
title = "Site-Specific Defect Detection in Composite Using Solitary Waves Based on Deep Learning",
abstract = "We propose a real-time non-destructive evaluation technique for defect detection in composites using highly nonlinear solitary waves (HNSWs) and a deep learning algorithm based on the convolution neural network (CNN). This technique implements deep learning to identify the presence of defects and classify the defect locations in the thickness direction of composites through HNSWs with strong energy intensity and non-distortive nature. To collect HNSW datasets for training and validation of the deep learning algorithm, AS4/PEEK composite specimens with artificial delamination are fabricated and HNSW datasets are generated from the experimental setup of a granular crystal sensor. Testing pretrained CNN based algorithms verifies the performance of detecting and classifying defects by location in composite plates.",
keywords = "AS4/PEEK, Convolution neural network, Delamination, Granular crystal, Machine learning, Non-destructive evaluation",
author = "Kim, {Tae Yeon} and Sangyoung Yoon and Yeun, {Chan Yeob} and Cantwell, {Wesley J.} and Cho, {Chung Suk}",
note = "Funding Information: The authors acknowledge support from Khalifa University Competitive Internal Research Award (CIRA) (No. CIRA-2019-009), Award No. RCII-2019-003, and the Center for Cyber-Physical Systems, Khalifa University, under Grant Number 8474000137-RC1-C2PS-T3. This research was also performed as part of the Aerospace Research and Innovation Center (ARIC) program which is jointly-funded by STRATA Manufacturing PJSC (a Mubadala company) and Khalifa University of Science and Technology. Funding Information: Acknowledgements. The authors acknowledge support from Khalifa University Competitive Internal Research Award (CIRA) (No. CIRA-2019-009), Award No. RCII-2019-003, and the Center for Cyber-Physical Systems, Khalifa University, under Grant Number 8474000137-RC1-C2PS-T3. This research was also performed as part of the Aerospace Research and Innovation Center (ARIC) program which is jointly-funded by STRATA Manufacturing PJSC (a Mubadala company) and Khalifa University of Science and Technology. Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 10th European Workshop on Structural Health Monitoring, EWSHM 2022 ; Conference date: 04-07-2022 Through 07-07-2022",
year = "2023",
doi = "10.1007/978-3-031-07322-9_45",
language = "British English",
isbn = "9783031073212",
series = "Lecture Notes in Civil Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "442--451",
editor = "Piervincenzo Rizzo and Alberto Milazzo",
booktitle = "European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 3",
address = "Germany",
}