The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An introduction to structural health monitoring
Abstract
The process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). Here, damage is defined as changes to the material and/or geometric properties of these systems, including changes to the boundary conditions and system connectivity, which adversely affect the system's performance. A wide variety of highly effective local non-destructive evaluation tools are available for such monitoring. However, the majority of SHM research conducted over the last 30 years has attempted to identify damage in structures on a more global basis. The past 10 years have seen a rapid increase in the amount of research related to SHM as quantified by the significant escalation in papers published on this subject. The increased interest in SHM and its associated potential for significant life-safety and economic benefits has motivated the need for this theme issue. This introduction begins with a brief history of SHM technology development. Recent research has begun to recognize that the SHM problem is fundamentally one of the statistical pattern recognition (SPR) and a paradigm to address such a problem is described in detail herein as it forms the basis for organization of this theme issue. In the process of providing the historical overview and summarizing the SPR paradigm, the subsequent articles in this theme issue are cited in an effort to show how they fit into this overview of SHM. In conclusion, technical challenges that must be addressed if SHM is to gain wider application are discussed in a general manner.
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Cites
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“Specific references are not cited, instead the reader is referred to Doebling et al. (1996), Sohn et al. (2003) and Randall (2004a,b) for more detailed summaries of this subject.”
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Research works printed but not linked: 22
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Cited by
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
Malekloo, A., Ozer, E., AlHamaydeh, M., & Girolami, M. (2022) · Structural Health Monitoring · doi:10.1177/14759217211036880 · Cited by 607
Abdeljaber, 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
Tapeh, A. T. G., & Naser, M. Z. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09793-w · Cited by 320
Martinez-Luengo, M., Kolios, A., & Wang, L. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.05.085 · Cited by 310
Metadata
- Authors
- Farrar, C. R., & Worden, K.
- 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
- 303-315
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2027456229
- Cited by
- 2,628
- References
- 1
- FWCI
- 110.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
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