Structural condition assessment of long-span suspension bridges using long-term monitoring data
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Deng et al. developed a six-order polynomial regression model to describe the correlations of frequency-temperature and displacement-temperature by using long-term monitoring data.
“Deng et al. [230] developed a six-order polynomial regression model to describe the correlations of frequency-temperature and displacement-temperature by using long-term monitoring data.”
From Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019 (2021) · cites this paper as [230]
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- Authors
- Yang, D., Youliang, D., & Aiqun, L.
- Affiliations
- Southeast University (CN)
- Corresponding author
- Youliang, Ding
- Venue
- Earthquake Engineering and Engineering Vibration
- Published
- 2010-03
- Volume
- 9
- Issue
- 1
- Pages
- 123-131
- ISSN
- 1671-3664 (ISSN-L)
- 1993-503X
- OpenAlex
- W2003844393
- Cited by
- 64
- References
- 10
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 5 · 2023: 9 · 2022: 2 · 2021: 3 · 2020: 6 · 2019: 4 · 2018: 6 · 2017: 4 · 2016: 2 · 2015: 7 · 2014: 2 · 2012: 5
- FWCI
- 8.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Earthquake Engineering and Engineering Vibration (publishedVersion)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Engineering and Vibration Analysis
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Engineering and Materials Analysis
- Keywords
- long-span suspension bridges, structural assessment, structural health monitoring, seasonal temperature effects, polynomial modeling, control charts, micro-damage detection, Runyang Suspension Bridge, online condition monitoring
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