NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials

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...

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Main Authors: Dongliang Guo, Lisha Zhou, Xingfa Luo
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/2/952
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author Dongliang Guo
Lisha Zhou
Xingfa Luo
author_facet Dongliang Guo
Lisha Zhou
Xingfa Luo
author_sort Dongliang Guo
collection DOAJ
description 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.
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spelling doaj-art-60ca1877c4d74d82b0abf310a434ca722025-01-24T13:21:28ZengMDPI AGApplied Sciences2076-34172025-01-0115295210.3390/app15020952NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite MaterialsDongliang Guo0Lisha Zhou1Xingfa Luo2The Key Laboratory for Software Engineering of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaThe Key Laboratory for Software Engineering of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaChongqing Academy of Agricultural Sciences, Nongke Avenue, Baishiyi Town, Jiulongpo District, Chongqing 400000, ChinaNon-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.https://www.mdpi.com/2076-3417/15/2/952visual analyticsmultimodal analysismaterial damagenon-destructive examination
spellingShingle Dongliang Guo
Lisha Zhou
Xingfa Luo
NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
Applied Sciences
visual analytics
multimodal analysis
material damage
non-destructive examination
title NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
title_full NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
title_fullStr NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
title_full_unstemmed NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
title_short NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
title_sort ndeexplorer visual analytics for exploring damage modes via multimodal data in the non destructive examination of composite materials
topic visual analytics
multimodal analysis
material damage
non-destructive examination
url https://www.mdpi.com/2076-3417/15/2/952
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AT lishazhou ndeexplorervisualanalyticsforexploringdamagemodesviamultimodaldatainthenondestructiveexaminationofcompositematerials
AT xingfaluo ndeexplorervisualanalyticsforexploringdamagemodesviamultimodaldatainthenondestructiveexaminationofcompositematerials