Structural Health Monitoring (SHM) methodologies are taking advantage of the development of the new families of MEMS sensors and of the progress in network technologies; future systems will rely on intelligent sensors performing locally data filtering, elaboration and model identification, connected over suitable buses. This paper describes some families of multivariate models that can be used in SHM–oriented identification procedures and, in particular, the extension of AR models known as AR+noise. It describes also the implementation of a new advanced SHM system, the Teleco SHM602, in the tower of the Engineering School of Bologna University and the multivariate models identified from the data collected by this system.

Structural monitoring of the Tower of the Faculty of Engineering in Bologna using MEMS-based sensing

GUIDORZI, ROBERTO;DIVERSI, ROBERTO;VINCENZI, LORIS;MAZZOTTI, CLAUDIO;
2011

Abstract

Structural Health Monitoring (SHM) methodologies are taking advantage of the development of the new families of MEMS sensors and of the progress in network technologies; future systems will rely on intelligent sensors performing locally data filtering, elaboration and model identification, connected over suitable buses. This paper describes some families of multivariate models that can be used in SHM–oriented identification procedures and, in particular, the extension of AR models known as AR+noise. It describes also the implementation of a new advanced SHM system, the Teleco SHM602, in the tower of the Engineering School of Bologna University and the multivariate models identified from the data collected by this system.
2011
Proceedings of the 8th International Conference on Structural Dynamics, EURODYN 2011
2499
2506
R. Guidorzi; R. Diversi; L. Vincenzi; C. Mazzotti; V. Simioli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/113270
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