Abstract
Bridge infrastructures in Europe are facing growing campaigns of maintenance plans, repairs and strengthening interventions to face progressive ageing, deterioration of materials, higher traffic loads with respect to the design assumptions, additional threats and hazards induced by the climate change as well as the results of inadequate periodic quality control. In this context, Structural Health Monitoring (SHM) systems are efficient tools to collect accurate data to support the application of preventive maintenance strategies as well as to support the informed management of transport infrastructures. Continuous SHM systems can provide a detailed characterization of the static and dynamic behavior of the bridge under service conditions, as well as being employed throughout the maintenance phase to deepen the knowledge of the structural response during the strengthening works. The data collection coupled with an updated numerical FE modelling of the bridge has the aim to confirm (or disconfirm) the assumptions made during the interventions design phase and to prove the actual efficiency of the repairs through an ongoing diagnosis process. This paper shows the use of Micro Electro Mechanical System (MEMS) sensors, both clinometers and accelerometers, for continuous SHM on a concrete bridge subject to service condition followed by strengthening works. A dense sensing monitoring approach is applied, where data are collected, analysed and compared with an updated digital twin finite element (FE) model of the bridge used to simulate the structural strengthening works as a reference. Attention is given to the bridge dynamic continuous response during the site activities, evaluated through Operational Modal Analysis (OMA) techniques, employed to control the expected effect of the structural interventions. This applied development in the domain of SHM shows the advantages of an industrial application of dense sensing techniques, to support both the service life as well as the maintenance phase of concrete bridges, to move towards a smarter and more efficient asset management process.
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