On estimating the accuracy of monitoring methods using Bayesian error propagation technique

Daniele Zonta; Federico Bruschetta; Carlo Cappello; R. Zandonini; Matteo Pozzi; Ming Wang; B. Glisic; D. Inaudi; D. Posenato; Y. Zhao

doi:10.1117/12.2046409

10 April 2014 On estimating the accuracy of monitoring methods using Bayesian error propagation technique

Daniele Zonta, Federico Bruschetta, Carlo Cappello, R. Zandonini, Matteo Pozzi, Ming Wang, B. Glisic, D. Inaudi, D. Posenato, Y. Zhao

Author Affiliations +

Proceedings Volume 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014; 90612B (2014) https://doi.org/10.1117/12.2046409
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2014, San Diego, California, United States

Abstract

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.

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Daniele Zonta, Federico Bruschetta, Carlo Cappello, R. Zandonini, Matteo Pozzi, Ming Wang, B. Glisic, D. Inaudi, D. Posenato, and Y. Zhao "On estimating the accuracy of monitoring methods using Bayesian error propagation technique", Proc. SPIE 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, 90612B (10 April 2014); https://doi.org/10.1117/12.2046409

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