Robust damage localization in plate-type structures by using an enhanced robust principal component analysis and data fusion technique
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PCA can reduce the data dimension.
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From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [258]
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Keshmiry, A., Hassani, S., Mousavi, M., & Dackermann, U. (2023) · Buildings · doi:10.3390/buildings13040918 · Cited by 96 · see citing works
- Authors
- Cao, S., Guo, N., & Xu, C.
- Affiliations
- Northwestern Polytechnical University (CN)
- Corresponding author
- Cao, Shancheng
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 162
- Pages
- 108091
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W3175914809
- Cited by
- 17
- References
- 47
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 5 · 2022: 5
- FWCI
- 1.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Mechanical Systems and Signal Processing (publishedVersion)
- Funders
- Natural Science Foundation of Shaanxi Province (2020JQ-109)
- Fundamental Research Funds for the Central Universities (3102019HTQD011)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Mechanics of Materials › Ultrasonics and Acoustic Wave Propagation
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Keywords
- damage localization, robust principal component analysis, data fusion, cosine similarity, full-field vibration measurement, measurement noise robustness, cantilever plate
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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