A Noise-Robust, Baseline-Free, and Adaptive Damage Indicator of Plate-like Structures Based on the Multicomponent Information Separation of High-Resolution Mode Shapes Using Wavelets Article Swipe
Yuexin Wang
,
Tongfa Deng
,
Jinwen Huang
,
Maosen Cao
,
Dragoslav Šumarac
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25092669
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25092669
Modal-based damage identification methods, particularly those utilizing mode shapes, excel in damage localization due to their spatial distribution characteristics. Traditional contact-based sensors often struggle with achieving high spatial resolution, while optical dynamic measurements, though high-resolution, are susceptible to environmental noise. This study proposes a novel multicomponent information separation (MIS) approach to overcome these challenges. The method decomposes mode shape information into noise, damage-related features, and waveform trends. The methodology begins with optical dynamic measurement to capture high-resolution mode shapes, followed by two-dimensional continuous wavelet transform (2D-CWT) for multiscale analysis. Adaptive wavelet scale selection via scale correlation analysis (SCA) improves noise separation, and an iterative weighted least squares fitting (IWLSF) method accurately fits the waveform trends. Finally, a noise-robust and baseline-free damage indicator (DI) is constructed through a difference operation to eliminate waveform trends, with damage localized at DI abrupt change positions. Validated through numerical simulations and experiments on damaged aluminum plates, the method demonstrates superior noise robustness and localization accuracy for multiple minor damages compared to existing wavelet-based approaches, showcasing its potential for advancing damage detection techniques.
Related Topics
Concepts
Robustness (evolution)
Wavelet
Waveform
Noise (video)
Computer science
Modal
Algorithm
Wavelet transform
Continuous wavelet transform
Artificial intelligence
Pattern recognition (psychology)
Discrete wavelet transform
Materials science
Chemistry
Polymer chemistry
Telecommunications
Image (mathematics)
Biochemistry
Radar
Gene
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25092669
- https://www.mdpi.com/1424-8220/25/9/2669/pdf?version=1745413996
- OA Status
- gold
- Cited By
- 1
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409730363
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409730363Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s25092669Digital Object Identifier
- Title
-
A Noise-Robust, Baseline-Free, and Adaptive Damage Indicator of Plate-like Structures Based on the Multicomponent Information Separation of High-Resolution Mode Shapes Using WaveletsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-04-23Full publication date if available
- Authors
-
Yuexin Wang, Tongfa Deng, Jinwen Huang, Maosen Cao, Dragoslav ŠumaracList of authors in order
- Landing page
-
https://doi.org/10.3390/s25092669Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/25/9/2669/pdf?version=1745413996Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/1424-8220/25/9/2669/pdf?version=1745413996Direct OA link when available
- Concepts
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Robustness (evolution), Wavelet, Waveform, Noise (video), Computer science, Modal, Algorithm, Wavelet transform, Continuous wavelet transform, Artificial intelligence, Pattern recognition (psychology), Discrete wavelet transform, Materials science, Chemistry, Polymer chemistry, Telecommunications, Image (mathematics), Biochemistry, Radar, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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