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Cited by 275

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Identification of bridge mode shapes using Short Time Frequency Domain Decomposition of the responses measured in a passing vehicle

Open access
Malekjafarian, A., OBrien, E.J.·2014·Engineering Structures

Abstract

Abstract This paper processes the signals from accelerometers mounted on a vehicle travelling over a bridge. Short Time Frequency Domain Decomposition (STFDD) is used to estimate bridge mode shapes from the dynamic response of the vehicle. In Frequency Domain Decomposition (FDD), several segments are defined on the bridge and the measurement is performed using two instrumented axles. Here, the FDD method is employed in a multi-stage procedure applied to the bridge segments in sequence. A rescaling process is used to construct the global mode shape vector. The performance of the proposed method is validated using numerical case studies. In other indirect bridge identification methods, the road profile may excite the vehicle, making it difficult to detect the bridge modes. This is addressed using two concepts: applying external excitation to the bridge and subtracting signals in the axles of successive trailers towed by the vehicle. The results obtained from the numerical investigation demonstrate that the proposed method can estimate the bridge mode shapes with acceptable accuracy. Sensitivity of the method to added white noise is also investigated.

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Crossref · 10.1016/j.engstruct.2014.10.007

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Metadata

Authors
Malekjafarian, A., & OBrien, E. J.
Venue
Engineering Structures
Publisher
Elsevier BV
Published
2014-12
Volume
81
Pages
386-397
ISSN
0141-0296 (ISSN-L)
OpenAlex
W1969377425
Cited by
275
References
38
FWCI
12.14
Type
journal article
Language
en
Open access
green

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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.