The present study describes an approach to boost the cost-effectiveness of the Operational Modal Analysis (OMA) application to historic buildings, through the optimisation of the trade-off between the number of required sensors and the quality of the information provided by them. Such an approach, currently under development and testing, considers a limited level of knowledge and relies on extensive simulations to assess the effect of the sources of uncertainties on the dynamic behaviour of the structure. In particular, the work focuses on a specific building typology, namely the noble palace overlooking Canal Grande in Venice, dating back to Gothic period. To this end, a prototype is defined based on the most relevant typological and morphological features of this typology, and its Finite Element (FE) model is generated. A Monte Carlo simulation technique is employed to sample several different instances from pre-set probabilistic functions for each stochastic variable. An Optimal Sensor Placement (OSP) algorithm is used to rank different recommended locations for a reduced number of sensors under these parameters’ variation, producing an optimal overall topology for the network. These considerations open future developments in view of a possible protocol applied to this historical building typology.

A Strategy of Optimal Sensor Placement for Dynamic Identification in Cultural Heritage

Salvatore Russo;Giacomo Imposa;
2023-01-01

Abstract

The present study describes an approach to boost the cost-effectiveness of the Operational Modal Analysis (OMA) application to historic buildings, through the optimisation of the trade-off between the number of required sensors and the quality of the information provided by them. Such an approach, currently under development and testing, considers a limited level of knowledge and relies on extensive simulations to assess the effect of the sources of uncertainties on the dynamic behaviour of the structure. In particular, the work focuses on a specific building typology, namely the noble palace overlooking Canal Grande in Venice, dating back to Gothic period. To this end, a prototype is defined based on the most relevant typological and morphological features of this typology, and its Finite Element (FE) model is generated. A Monte Carlo simulation technique is employed to sample several different instances from pre-set probabilistic functions for each stochastic variable. An Optimal Sensor Placement (OSP) algorithm is used to rank different recommended locations for a reduced number of sensors under these parameters’ variation, producing an optimal overall topology for the network. These considerations open future developments in view of a possible protocol applied to this historical building typology.
2023
9783031396021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11578/356309
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