Structural monitoring of a tower by means of MEMS-based sensing and enhanced autoregressive models

Structural Health Monitoring (SHM) methodologies are taking advantage of the development of new families of MEMS sensors and of the available network technologies. Advanced systems rely on intelligent bus-connected sensing units performing locally data filtering, elaboration and model identification. This paper describes a family of enhanced multivariate autoregressive models that can be used in SHM-oriented identification procedures and the implementation of a new advanced SHM system in the tower of the Engineering School of Bologna University. It describes also the results given by the considered procedure and a comparison of the implemented MEMS-based system with a traditional solution based on piezoelectric seismic accelerometers.