The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Damage identification using inverse methods
Abstract
This paper gives an overview of the use of inverse methods in damage detection and location, using measured vibration data. Inverse problems require the use of a model and the identification of uncertain parameters of this model. Damage is often local in nature and although the effect of the loss of stiffness may require only a small number of parameters, the lack of knowledge of the location means that a large number of candidate parameters must be included. This paper discusses a number of problems that exist with this approach to health monitoring, including modelling error, environmental effects, damage localization and regularization.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
Traffic-induced variability in dynamic properties of cable-stayed bridge
Zhang, Q. W., Fan, L. C., & Yuan, W. C. (2002) · Earthquake Engineering & Structural Dynamics · doi:10.1002/eqe.204 · Cited by 73
Cited by
Malekloo, A., Ozer, E., AlHamaydeh, M., & Girolami, M. (2022) · Structural Health Monitoring · doi:10.1177/14759217211036880 · Cited by 607
Martinez-Luengo, M., Kolios, A., & Wang, L. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.05.085 · Cited by 310
Cofre-Martel, S., Kobrich, P., Lopez Droguett, E., & Meruane, V. (2019) · Shock and Vibration · doi:10.1155/2019/9859281 · Cited by 65
Raviolo, D., Civera, M., & Zanotti Fragonara, L. (2023) · Buildings · doi:10.3390/buildings13123010 · Cited by 24
Metadata
- Authors
- Friswell, M. I.
- 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
- 393-410
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2105396578
- Cited by
- 376
- References
- 2
- FWCI
- 52.17
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Damage identification using inverse methods. https://app.cochat.ai/papers/10.1098/rsta.2006.1930
- The paper
- Friswell, M. I. (2007). Damage identification using inverse methods. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. https://doi.org/10.1098/rsta.2006.1930
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
