Ponte Moesa Campagnola bridge - Artificial damage scenarios - Monitoring report [report]

Martakis Panagiotis, Yves Reuland, Eleni Chatzi
2022 Zenodo  
This document reports on the conceptualization, installation procedure and the cumulative results of the monitoring campaign conducted on the Ponte Moesa Campagnola (TI). This study enables the evaluation of monitoring technologies and associated data-driven analysis methods, applied for damage assessment of a real-world structure. The structure forms a typical sample of bridges in the Swiss Roadway Network, comprising a representative sample of a traditional concrete bridge engineering
more » ... . The monitoring campaign comprises two phases: Phase I – Monitoring during Controlled Damage. In this phase, conducted in November 2019, measurements and non-destructive-evaluation techniques have been applied on the bridge, while localized damage scenarios have been artificially introduced. This report is concerned with the analysis of the continuous monitoring technologies, namely the processing of data obtained from accelerometers and strain sensors. The report on the use of Non-Destructive Evaluation (NDE) technologies, such as Ground Penetrating Radar (GPR) and Ultrasound scans, is offered in the separate report R191102, compiled by our partner recontec. The obtained results in this phase, clearly indicate the potential of continuous monitoring methods (relying on measurements of acceleration and strain) for quantifying the effect of the controllably induced artificial damages on the bridge. These artificial damages were chosen to represent structural faults of increasing intensity. Phase II – Monitoring during Demolition. In this phase, executed in January 2020, lower cost accelerometer sensors were used to check the tracking of damage evolution during demolition. In both phases, the derivation of clear indicators of damage, which cannot only detect but also locale damage for such typical bridge structures, demonstrates the clear value of Structural Health Monitoring (SHM) for the efficient management of ageing infrastructure, since the derived Damage Indicators be exploited to support decisions on m [...]
doi:10.5281/zenodo.6756889 fatcat:hwyxjcoqjfddpccoifw4rzzcba