Wavelet-based vibration denoising for structural health monitoring Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.1007/s44285-024-00025-0
In the context of civil engineering applications, vibration responses are complex, exhibiting variations in time and space and often containing nonlinearity and uncertainties not considered during data collection. These responses can also be contaminated by various sources, impacting damage identification processes. A significant challenge is how to effectively remove noise from these data to obtain reliable damage indicators that are unresponsive to noise and environmental factors.This study proposes a new denoising algorithm based on discrete wavelet transform (DWT) that addresses this issue. The suggested method offers a strategy for denoising using distinct thresholds for positive and negative coefficient values at each band and applying denoising process to both detail and trend components. The results prove the effectiveness of the technique and show that Bayes thresholding performs better than the other techniques in terms of the evaluated metrics. This suggests that Bayes thresholding is a more accurate and robust technique for thresholding compared to other common techniques.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s44285-024-00025-0
- OA Status
- diamond
- Cited By
- 5
- References
- 42
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4404147698Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s44285-024-00025-0Digital Object Identifier
- Title
-
Wavelet-based vibration denoising for structural health monitoringWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-07Full publication date if available
- Authors
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Ahmed Silik, Mohammad Noori, Zhishen Wu, Wael A. Altabey, Ji Dang, Nabeel S. D. FarhanList of authors in order
- Landing page
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https://doi.org/10.1007/s44285-024-00025-0Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1007/s44285-024-00025-0Direct OA link when available
- Concepts
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Wavelet, Structural health monitoring, Noise reduction, Computer science, Artificial intelligence, Vibration, Pattern recognition (psychology), Acoustics, Structural engineering, Engineering, PhysicsTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 5Per-year citation counts (last 5 years)
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42Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2016534479, https://openalex.org/W1974001681, https://openalex.org/W2610617322, https://openalex.org/W2059099907, https://openalex.org/W2000284541, https://openalex.org/W2010671860, https://openalex.org/W3080652136, https://openalex.org/W2000982976, https://openalex.org/W2007221293, https://openalex.org/W163612977, https://openalex.org/W2125056386, https://openalex.org/W3094645401, https://openalex.org/W2120390927, https://openalex.org/W3161248018, https://openalex.org/W2221128418, https://openalex.org/W3087849610, https://openalex.org/W4386744312, https://openalex.org/W1993109727, https://openalex.org/W2139155691, https://openalex.org/W2168312801, https://openalex.org/W3194893232, https://openalex.org/W2144542677, https://openalex.org/W2168105211, https://openalex.org/W2163690745, https://openalex.org/W2163621334, https://openalex.org/W2124335859, https://openalex.org/W1985110006, https://openalex.org/W2149072817, https://openalex.org/W1970352604, https://openalex.org/W2132984323, https://openalex.org/W1538498264, https://openalex.org/W3169147854, https://openalex.org/W2115755118, https://openalex.org/W2106515586, https://openalex.org/W2157856927, https://openalex.org/W4321352163, https://openalex.org/W2079724595, https://openalex.org/W2158940042, https://openalex.org/W3142026135, https://openalex.org/W2108078404, https://openalex.org/W2033484654, https://openalex.org/W2082076175 |
| referenced_works_count | 42 |
| abstract_inverted_index.A | 42 |
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| corresponding_author_ids | https://openalex.org/A5074630329 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I149919469 |
| citation_normalized_percentile.value | 0.83555793 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |