Mode shapes are sensitive to the structural condition of bridges but a reasonable estimate of such changes require several accelerometers, which can be resource intensive. This paper obviates this problem through a novel structure health monitoring (SHM) approach for estimating modal parameters of bridges, including damage-induced changes of boundary conditions by using progressively re-deploying sensors along a monitored bridge. This concept of re-deployable sensors and subsequent use of a series of measurements allow extracting data from different bridge segments and also to get an indication of the condition of the bridge through frequency domain decomposition. Data from different segments are combined to estimate the global mode shape of the bridge and its gradient is observed to be indicative of support stiffness change. The concept is successfully tested through a full-scale field trial on a railway bridge in the Republic of Ireland, before and after the rehabilitation of its supports. The results are expected to guide future on-site measurement of damages due to flooding, scour, and other natural hazards, along with the effectiveness of intervention actions like repair and rehabilitation, providing a clear evidence base for practical value of SHM.
Bibliographical noteFunding Information:
This research has received funding from Science Foundation Ireland (SFI) under the US-Ireland R&D partnership with the National Science Foundation (NSF) and Invest Northern Ireland (ID: 16/US/13277). The authors thank Irish Rail for their support and for permission to perform field testing in Galway, Ireland. Vikram Pakrashi and Eugene OBrien would like to thank EU-funded SIRMA (Strengthening Infrastructure Risk Management in the Atlantic Area) project (Grant No. EAPA\_826/2018).
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- damage detection
- mode shapes
- re-deployable sensors
- structural health monitoring
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Safety, Risk, Reliability and Quality
- Geotechnical Engineering and Engineering Geology
- Ocean Engineering
- Mechanical Engineering
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Development of a Minimal Information Data - modelling approach for the monitoring of short and medium span bridgesAuthor: O'Higgins, C., Jul 2022
Supervisor: McGetrick, P. (Supervisor), Robinson, D. (Supervisor) & Hester, D. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of PhilosophyFile