NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Structural Health Monitoring Techniques · Ultrasonics and Acoustic Wave Propagation · Infrastructure Maintenance and Monitoring
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
The Key Laboratory for Software Engineering of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
Chongqing Academy of Agricultural Sciences, Nongke Avenue, Baishiyi Town, Jiulongpo District, Chongqing 400000, China
Funding
National Science Foundation of China · Natural Science Foundation of Hebei Province · Innovation Capability Improvement Plan Project of Hebei Province
References (45)
Show source-provided references
1. Polymer composite materials: A comprehensive review10.1016/j.compstruct.2021.113640 ↗
2. Sustainability in the manufacturing of composite materials: A literature review and directions for future research10.1016/j.jmapro.2022.12.020 ↗
3. Recent advancements in thermoplastic composite materials in aerospace industry10.1177/08927057231222820 ↗
4. Cracks, microcracks and fracture in polymer structures: Formation, detection, autonomic repair10.1016/j.pmatsci.2016.07.007 ↗
5. Tunable crack propagation behavior in carbon fiber reinforced plastic laminates with polydopamine and graphene oxide treated fibers10.1016/j.matdes.2016.10.013 ↗
6. Guided ultrasonic waves for non-destructive monitoring of the stress levels in prestressed steel strands10.1016/j.ultras.2008.07.009 ↗
7. Non-destructive evaluation of concrete using a capacitive imaging technique: Preliminary modelling and experiments10.1016/j.cemconres.2010.08.015 ↗
8. Niezrecki, C., Baqersad, J., and Sabato, A. (2018). Digital image correlation techniques for non-destructive evaluation and structural health monitoring. Handbook of Advanced Non-Destructive Evaluation, Springer.10.1007/978-3-319-30050-4_47-1 ↗
9. Advances, limitations and prospects of nondestructive testing and evaluation of thick composites and sandwich structures: A state-of-the-art review10.1016/j.compstruct.2020.112951 ↗
10. Cluster analysis of acoustic emission signals and infrared thermography for defect evolution analysis of glass/epoxy composites10.1016/j.infrared.2020.103581 ↗
11. On strength prediction of laminated composites10.1016/j.compscitech.2021.109206 ↗
12. Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review10.1177/1687814020913761 ↗
13. Damage characterization of CFRP laminates using acoustic emission and digital image correlation: Clustering, damage identification and classification10.1016/j.engfracmech.2022.108993 ↗
14. Experimental study on damage and fracture characteristics of Beishan granite subjected to high-temperature treatment with DIC and AE techniques10.1007/s00603-020-02271-4 ↗
15. Quantitative acoustic emission and failure mechanics of composite materials10.1016/0041-624X(87)90033-3 ↗
16. Characterisation of drilling-induced damage in GFRP Honeycomb Sandwich Composites using Acoustic Emission10.1016/j.promfg.2021.06.066 ↗
17. Cluster analysis of acoustic emission signals for tensile damage characterization of quasi-static indented carbon/glass fiber-reinforced hybrid laminate composites10.1016/j.compositesa.2021.106597 ↗
18. Use of acoustic emission to identify damage modes in glass fibre reinforced polyester10.1016/S0266-3538(02)00087-8 ↗
19. Pattern recognition approach to identify natural clusters of acoustic emission signals10.1016/j.patrec.2011.09.018 ↗
20. Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clustering10.1177/0021998311425968 ↗
21. Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm10.1177/0731684412442257 ↗
22. Feasibility and limitations of damage identification in composite materials using acoustic emission10.1016/j.compositesa.2015.05.003 ↗
23. Damage assessment of composite structures using digital image correlation10.1007/s10443-013-9352-5 ↗
24. Strength prediction and progressive failure analysis of carbon fiber reinforced polymer laminate with multiple interacting holes involving three dimensional finite element analysis and digital image correlation10.1177/1056789513504123 ↗
25. Gray change detection method for damage monitoring in materials10.1364/AO.54.000934 ↗
26. Digital image correlation (DIC) based damage detection for CFRP laminates by using machine learning based image semantic segmentation10.1016/j.ijmecsci.2022.107529 ↗
27. Full-field strain measurements for validation of meso-FE analysis of textile composites10.1016/j.compositesa.2007.09.011 ↗
28. Suarez, E., Sause, M.G.R., and Gallego, A. (2016, January 5–9). Influence of an optical fiber embedded on unidirectional CFRP laminates evaluated with the Acoustic Emission and 3D Digital Image Correlation techniques. Proceedings of the Progress in Acoustic Emission XVIII, Kyoto, Japan.
29. Heinzl, C., Amirkhanov, A., and Kastner, J. (2018). Processing, analysis and visualization of CT data. Industrial X-Ray Computed Tomography, Springer.10.1007/978-3-319-59573-3_4 ↗
30. Chen, J., Yu, Z., and Jin, H. (2022). Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review. Front. Mater., 9.10.3389/fmats.2022.986645 ↗
31. Critical insights into the state-of-the-art NDE data fusion techniques for the inspection of structural systems10.1002/stc.2857 ↗
32. STAR: Visual Computing in Materials Science10.1111/cgf.13214 ↗
33. Weissenböck, J., Amirkhanov, A., Li, W., Reh, A., Amirkhanov, A., Gröller, E., Kastner, J., and Heinzl, C. (2014, January 4–7). FiberScout: An interactive tool for exploring and analyzing fiber reinforced polymers. Proceedings of the 2014 IEEE Pacific Visualization Symposium, Yokohama, Japan.10.1109/PacificVis.2014.52 ↗
34. Zobel, V., Stommel, M., and Scheuermann, G. (2015, January 25–30). Feature-based tensor field visualization for fiber reinforced polymers. Proceedings of the 2015 IEEE Scientific Visualization Conference (SciVis), Chicago, IL, USA.10.1109/SciVis.2015.7429491 ↗
35. Residual strength and damage characterization of repaired glass/epoxy composite laminates using AE and DIC10.1016/j.compstruct.2016.05.005 ↗
36. In-situ damage monitoring of a SiC/SiC ceramic matrix composite using acoustic emission and digital image correlation10.1016/j.compstruct.2016.09.040 ↗
37. ECharts: A declarative framework for rapid construction of web-based visualization10.1016/j.visinf.2018.04.011 ↗
38. Matplotlib: A 2D Graphics Environment10.1109/MCSE.2007.55 ↗
39. (2021). Standard Test Method for Primary Calibration of Acoustic Emission Sensors (Standard No. ASTM E1106-21).
40. Acoustic emission monitoring of damage progression in glass/epoxy composites during static and fatigue tensile tests10.1016/j.apacoust.2017.11.017 ↗
41. Damage mode identification of open hole composite laminates based on acoustic emission and digital image correlation methods10.1016/j.compstruct.2021.114299 ↗
42. Ncorr: Open-source 2D digital image correlation matlab software10.1007/s11340-015-0009-1 ↗
43. Multimodal machine learning: A survey and taxonomy
44. Visualization and visual analysis of multifaceted scientific data: A survey10.1109/TVCG.2012.110 ↗
45. Borgo, R., Kehrer, J., Chung, D.H., Maguire, E., Laramee, R.S., Hauser, H., Ward, M., and Chen, M. (2024, December 15). Glyph-Based Visualization: Foundations, Design Guidelines, Techniques and Applications. Eurographics (State of the Art Reports). Available online: http://cronfa.swan.ac.uk/Record/cronfa24643.