Bridge vertical deflection evaluation using clinometers data obtained by Micro Electro-Mechanical Systems (MEMS) sensors

This paper presents a bridge deflection measurement method based on data acquired by Micro Electro-Mechanical Systems (MEMS) sensors. The study shows a clinometer-based deflection curve method which can reconstruct the deflected shapes of bridges directly from acquired data. This work is supported by data collected from laboratory loading tests performed at University of Rome “Tor Vergata” on full scale reinforced concrete beams simulating the girders of a bridge. A data processing method based on polynomial functions was used to reconstruct the effective displacements of the structures. This new method based on data acquired by MEMS sensors does not need fixed observation points as other deflection measurement methods because the clinometers are installed on the structure directly. The goal is to build an artificial intelligence algorithm that starting from data acquired from the sensors in real time can monitor a bridge deflection and predict its future behaviour.