TY - GEN
T1 - Sensor fusion on structural monitoring data analysis
T2 - 10th International Conference on Damage Assessment of Structures, DAMAS 2013
AU - Zonta, Daniele
AU - Bruschetta, Federico
AU - Zandonini, Riccardo
AU - Pozzi, Matteo
AU - Ming-Wang,
AU - Glisic, Branko
AU - Inaudi, Daniele
AU - Posenato, Daniele
AU - Yang-Zhao,
N1 - Funding Information:
assistance during the experiments as well as to M. Wolff for the numerical estimate of n2. This work was supported by the European Commission under ESPRIT Project No. 20029 (ACQUIRE).
PY - 2013
Y1 - 2013
N2 - This paper illustrates an application of Bayesian logic to monitoring data analysis and structural condition state inference. The case study is a 260 m 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-term load 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.
AB - This paper illustrates an application of Bayesian logic to monitoring data analysis and structural condition state inference. The case study is a 260 m 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-term load 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.
KW - Bayesian inference
KW - Cable-Stayed bridge
KW - Elasto-magnetic sensors
KW - Fiber optic sensors
UR - http://www.scopus.com/inward/record.url?scp=84883724605&partnerID=8YFLogxK
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U2 - 10.4028/www.scientific.net/KEM.569-570.812
DO - 10.4028/www.scientific.net/KEM.569-570.812
M3 - Conference contribution
AN - SCOPUS:84883724605
SN - 9783037857960
T3 - Key Engineering Materials
SP - 812
EP - 819
BT - Damage Assessment of Structures X
PB - Trans Tech Publications Ltd
Y2 - 8 July 2013 through 10 July 2013
ER -