Bayesian analysis of monitoring data from cable-stayed bridge

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Zonta, D. and Bruschetta, F. and Zandonini, R. and Pozzi, M. and Glisic, B. and Wang, M. L. and Zhao, Y. and Inaudi, D. and Posenato, D.; Deodatis, George and Ellingwood, Bruce R and Frangopol, Dan M, eds. (2014) Bayesian analysis of monitoring data from cable-stayed bridge. In: Safety, reliability, risk and life-cycle performance of structures and Infrastructures. CRC Press/Balkema, USA, pp. 2465-2470. ISBN 9781138000865

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Abstract

This paper illustrates an application of Bayesian logic to monitoring data analysis and structural condition state inference. The case study is a 260m long cable-stayed bridge spanning the Adige River 10 km north of the town of Trento, Italy. This is a statically indeterminate structure, having a composite steel-concrete deck, supported by 12 stay cables. Structural redundancy, possible relaxation losses and an as-built condition differing from design, suggest that long-termload redistribution between cables can be expected.To monitor load redistribution, the owner decided to install a monitoring system which combines built-on-site elasto-magnetic and fiber-optic sensors. In this note, we discuss a rational way to improve the accuracy of the load estimate from the EM sensors taking advantage of the FOS information. More specifically, we use a multi-sensor Bayesian data fusion approach which combines the information from the two sensing systems with the prior knowledge, including design information and the outcomes of laboratory calibration. Using the data acquired to date, we demonstrate that combining the two measurements allows a more accurate estimate of the cable load, to better than 50 kN.

ORCID iDs

Zonta, D. ORCID logoORCID: https://orcid.org/0000-0002-7591-9519, Bruschetta, F., Zandonini, R., Pozzi, M., Glisic, B., Wang, M. L., Zhao, Y. ORCID logoORCID: https://orcid.org/0000-0002-7728-553X, Inaudi, D. and Posenato, D.; Deodatis, George, Ellingwood, Bruce R and Frangopol, Dan M
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