Tabatabaeian, A., Jerkovic, B., Harrison, P. , Marchiori, E. and Fotouhi, M. (2023) Barely visible impact damage detection in composite structures using deep learning networks with varying complexities. Composites Part B: Engineering, 264, 110907. (doi: 10.1016/j.compositesb.2023.110907)
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Abstract
Visual inspection is one of the most common non-destructive testing (NDT) methods that offers a fast evaluation of surface damage in aerospace composite structures. However, it is highly dependent on human-related factors and may not detect barely visible impact damage (BVID). In this research, low velocity impact tests with different energy levels are conducted on two groups of composite panels, namely ‘reference’ and ‘sensor-integrated’ samples. Then, the results of impact tests, together with C-scan and visual inspection images, are analysed to define the BVID range and create an original image dataset. Next, four different deep learning models are trained, validated and tested to capture the BVID only from the images of the impacted and non-impacted surfaces. The results show that all four networks can learn and detect BVID quite well, and the sensor-integrated samples reduce the training time and improve the accuracy of deep learning models. ResNet outperforms other networks with the highest accuracy of 96.2% and 98.36% on the back-face of reference and sensor-integrated samples, respectively. The proposed damage recognition method can act as a fast, inexpensive and accurate structural health monitoring tool for composite structures in real-life applications.
| Item Type: | Articles |
|---|---|
| Additional Information: | The authors are grateful to the Radboud-Glasgow partnership scheme for supporting this work. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Fotouhi, Dr Mohammad and Harrison, Dr Philip and Tabatabaeian, Mr Ali |
| Creator Roles: | Tabatabaeian, A.Conceptualization, Investigation, Methodology, Data curation, Formal analysis, Visualization, Writing – original draft, Writing – review and editing Harrison, P.Supervision, Writing – review and editing Fotouhi, M.Project administration, Supervision, Writing – review and editing, Funding acquisition |
| Authors: | Tabatabaeian, A., Jerkovic, B., Harrison, P., Marchiori, E., and Fotouhi, M. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | Composites Part B: Engineering |
| Publisher: | Elsevier |
| ISSN: | 1359-8368 |
| ISSN (Online): | 1879-1069 |
| Published Online: | 26 July 2023 |
| Copyright Holders: | Copyright © 2023 The Authors |
| First Published: | First published in Composites Part B: Engineering 264:10.1016/j.compositesb.2023.110907 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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