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Damage prognosis: the future of structural health monitoring
Abstract
This paper concludes the theme issue on structural health monitoring (SHM) by discussing the concept of damage prognosis (DP). DP attempts to forecast system performance by assessing the current damage state of the system (i.e. SHM), estimating the future loading environments for that system, and predicting through simulation and past experience the remaining useful life of the system. The successful development of a DP capability will require the further development and integration of many technology areas including both measurement/processing/telemetry hardware and a variety of deterministic and probabilistic predictive modelling capabilities, as well as the ability to quantify the uncertainty in these predictions. The multidisciplinary and challenging nature of the DP problem, its current embryonic state of development, and its tremendous potential for life-safety and economic benefits qualify DP as a ‘grand challenge’ problem for engineers in the twenty-first century.
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Citations
Cited by
Martinez-Luengo, M., Kolios, A., & Wang, L. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.05.085 · Cited by 310
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
The Adoption of Prognostic Technologies in Maintenance Decision Making: A Multiple Case Study
Tiddens, W. W., Braaksma, A. J. J., & Tinga, T. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.08.028 · Cited by 38
Metadata
- Authors
- Farrar, C. R., & Lieven, N. A. J.
- Venue
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2006-12-12
- Volume
- 365
- Issue
- 1851
- Pages
- 623-632
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2162394527
- Cited by
- 448
- References
- 0
- FWCI
- 42.03
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
