Bayesian analysis of monitoring data from cable-stayed bridge

D. Zonta, F. Bruschetta, R. Zandonini, M. Pozzi, B. Glisic, M. L. Wang, Y. Zhao, D. Inaudi, D. Posenato

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)

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.

LanguageEnglish
Title of host publicationSafety, reliability, risk and life-cycle performance of structures and Infrastructures
Subtitle of host publicationproceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013
EditorsGeorge Deodatis, Bruce R Ellingwood, Dan M Frangopol
Pages2465-2470
Number of pages6
Publication statusPublished - 10 Feb 2014
Event11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 - New York, NY, United States
Duration: 16 Jun 201320 Jun 2013

Conference

Conference11th International Conference on Structural Safety and Reliability, ICOSSAR 2013
CountryUnited States
CityNew York, NY
Period16/06/1320/06/13

Fingerprint

Cable stayed bridges
Cables
Monitoring
Sensors
Fiber optic sensors
Data fusion
Redundancy
Rivers
Calibration
Concretes
Steel
Composite materials

Keywords

  • Bayesian analysis
  • cable stayed bridge
  • data monitoring

Cite this

Zonta, D., Bruschetta, F., Zandonini, R., Pozzi, M., Glisic, B., Wang, M. L., ... Posenato, D. (2014). Bayesian analysis of monitoring data from cable-stayed bridge. In G. Deodatis, B. R. Ellingwood, & D. M. Frangopol (Eds.), Safety, reliability, risk and life-cycle performance of structures and Infrastructures: proceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013 (pp. 2465-2470)
Zonta, D. ; Bruschetta, F. ; Zandonini, R. ; Pozzi, M. ; Glisic, B. ; Wang, M. L. ; Zhao, Y. ; Inaudi, D. ; Posenato, D. / Bayesian analysis of monitoring data from cable-stayed bridge. Safety, reliability, risk and life-cycle performance of structures and Infrastructures: proceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013. editor / George Deodatis ; Bruce R Ellingwood ; Dan M Frangopol. 2014. pp. 2465-2470
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title = "Bayesian analysis of monitoring data from cable-stayed bridge",
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.",
keywords = "Bayesian analysis, cable stayed bridge, data monitoring",
author = "D. Zonta and F. Bruschetta and R. Zandonini and M. Pozzi and B. Glisic and Wang, {M. L.} and Y. Zhao and D. Inaudi and D. Posenato",
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Zonta, D, Bruschetta, F, Zandonini, R, Pozzi, M, Glisic, B, Wang, ML, Zhao, Y, Inaudi, D & Posenato, D 2014, Bayesian analysis of monitoring data from cable-stayed bridge. in G Deodatis, BR Ellingwood & DM Frangopol (eds), Safety, reliability, risk and life-cycle performance of structures and Infrastructures: proceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013. pp. 2465-2470, 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013, New York, NY, United States, 16/06/13.

Bayesian analysis of monitoring data from cable-stayed bridge. / Zonta, D.; Bruschetta, F.; Zandonini, R.; Pozzi, M.; Glisic, B.; Wang, M. L.; Zhao, Y.; Inaudi, D.; Posenato, D.

Safety, reliability, risk and life-cycle performance of structures and Infrastructures: proceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013. ed. / George Deodatis; Bruce R Ellingwood; Dan M Frangopol. 2014. p. 2465-2470.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

TY - GEN

T1 - Bayesian analysis of monitoring data from cable-stayed bridge

AU - Zonta, D.

AU - Bruschetta, F.

AU - Zandonini, R.

AU - Pozzi, M.

AU - Glisic, B.

AU - Wang, M. L.

AU - Zhao, Y.

AU - Inaudi, D.

AU - Posenato, D.

PY - 2014/2/10

Y1 - 2014/2/10

N2 - 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.

AB - 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.

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KW - data monitoring

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M3 - Conference contribution book

SN - 9781138000865

SP - 2465

EP - 2470

BT - Safety, reliability, risk and life-cycle performance of structures and Infrastructures

A2 - Deodatis, George

A2 - Ellingwood, Bruce R

A2 - Frangopol, Dan M

ER -

Zonta D, Bruschetta F, Zandonini R, Pozzi M, Glisic B, Wang ML et al. Bayesian analysis of monitoring data from cable-stayed bridge. In Deodatis G, Ellingwood BR, Frangopol DM, editors, Safety, reliability, risk and life-cycle performance of structures and Infrastructures: proceedings of the 11th International Conference on Structural Safety and Reliability, New York, USA, 16-20 June 2013. 2014. p. 2465-2470