Academic Journal
NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
| Title: | NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials |
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| Authors: | Dongliang Guo, Lisha Zhou, Xingfa Luo |
| Source: | Applied Sciences, Vol 15, Iss 2, p 952 (2025) |
| Publisher Information: | MDPI AG, 2025. |
| Publication Year: | 2025 |
| Collection: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| Subject Terms: | visual analytics, multimodal analysis, material damage, non-destructive examination, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| More Details: | Non-destructive examination (NDE) in the field of materials engineering is a technique based on acoustics and optical principles used for detecting and evaluating internal defects in materials without causing any damage. The majority of current research on material damage focuses on the analysis of a single NDE method, resulting in low correlation between different NDE methods, and their results are frequently presented as complex data and images, making it difficult for professionals to obtain intuitive inspection results. Therefore, we propose a visual analytics system, NDEExplorer, aimed at solving these problems through visual analytics techniques. The system supports the use of two NDE methods, Acoustic Emission (AE) and Digital Image Correlation (DIC), providing interactive and intuitive views for observing composite material damage features. In addition, the system features a fusion analysis approach and a view that combines AE and DIC methods, enabling users to explore the correlations and trends in multimodal data generated during the material damage process. For users, the application of this system can help accurately identify the various material damage stages and their accompanying damage modes. To evaluate the effectiveness of the proposed method, we conduct a case study using two modal datasets from the same composite material damage scenario and carry out qualitative interviews with professionals and graduate students in the field. Finally, the quantitative feedback from a user study confirms the usefulness of our visual system for the multimodal analysis of material damage datasets. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/15/2/952; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app15020952 |
| Access URL: | https://doaj.org/article/60ca1877c4d74d82b0abf310a434ca72 |
| Accession Number: | edsdoj.60ca1877c4d74d82b0abf310a434ca72 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20763417 |
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| DOI: | 10.3390/app15020952 |
| Published in: | Applied Sciences |
| Language: | English |