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Structural Health Monitoring Using Statistical Pattern Recognition Techniques
Abstract
This paper casts structural health monitoring in the context of a statistical pattern recognition paradigm. Two pattern recognition techniques based on time series analysis are applied to fiber optic strain gauge data obtained from two different structural conditions of a surface-effect fast patrol boat. The first technique is based on a two-stage time series analysis combining Auto-Regressive (AR) and Auto-Regressive with eXogenous inputs (ARX) prediction models. The second technique employs an outlier analysis with the Mahalanobis distance measure. The main objective is to extract features and construct a statistical model that distinguishes the signals recorded under the different structural conditions of the boat. These two techniques were successfully applied to the patrol boat data clearly distinguishing data sets obtained from different structural conditions.
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Citations
Cited by
Emerging Artificial Intelligence Methods in Structural Engineering
Salehi, H., & Burgueño, R. (2018) · Engineering Structures · doi:10.1016/j.engstruct.2018.05.084 · Cited by 1,068
Effects of environmental and operational variability on structural health monitoring
Sohn, H. (2007) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2006.1935 · Cited by 883
Self-citationAbdeljaber, O., Avci, O., Kiranyaz, M. S., Boashash, B., Sodano, H., & Inman, D. J. (2018) · Neurocomputing · doi:10.1016/j.neucom.2017.09.069 · Cited by 521
Structural damage identification using damping: a compendium of uses and features
Cao, M. S., Sha, G. G., Gao, Y. F., & Ostachowicz, W. (2017) · Smart Materials and Structures · doi:10.1088/1361-665x/aa550a · Cited by 196
Cross, E. J., Worden, K., & Chen, Q. (2011) · Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rspa.2011.0023 · Cited by 173
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Metadata
- Authors
- Sohn, H., Farrar, C. R., Hunter, N. F., & Worden, K.
- Venue
- Journal of Dynamic Systems, Measurement, and Control
- Publisher
- ASME International
- Published
- 2001-02-07
- Volume
- 123
- Issue
- 4
- Pages
- 706-711
- ISSN
- 0022-0434 (ISSN-L)
- 1528-9028
- OpenAlex
- W2009600269
- Cited by
- 402
- References
- 0
- FWCI
- 43.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Sohn, H., Farrar, C. R., Hunter, N. F., & Worden, K. (2001). Structural Health Monitoring Using Statistical Pattern Recognition Techniques. Journal of Dynamic Systems, Measurement, and Control. https://doi.org/10.1115/1.1410933
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
