Abstract
Structural monitoring plays a central role in civil engineering; in particular, optimal sensor positioning is essential for correct monitoring both in terms of usable data and for optimizing the cost of the setup sensors. In this context, we focus our attention on the identification of the dynamic response of beam-like structures with uncertain damages. In particular, the non-localized damage is described using a Gaussian distributed random damage parameter. Furthermore, a procedure for selecting an optimal number of sensor placements has been presented based on the comparison among the probability of damage occurrence and the probability to detect the damage, where the former can be evaluated from the known distribution of the random parameter, whereas the latter is evaluated exploiting the closed-form asymptotic solution provided by a perturbation approach. The presented case study shows the capability and reliability of the proposed procedure for detecting the minimum number of sensors such that the monitoring accuracy (estimated by an error function measuring the differences among the two probabilities) is not greater than a control small value.
Highlights
Strategic constructions, such as bridges and tower buildings, during their lifetime are inexorably subjected to degradation and damage of various kinds
The results obtained by the authors show the importance of considering the second order terms of the perturbation approach in order to achieve a significant increase in the identifiability of stochastic damages
The beam model is non-deformable for any shear deformation and changes in mass due to structural damages are assumed negligible
Summary
Strategic constructions, such as bridges and tower buildings, during their lifetime are inexorably subjected to degradation and damage of various kinds For this reason, careful monitoring is required for profitable maintenance and for activation of safety protocols in case of danger (“early warning” systems). The main problem, that discourages the use of large-scale structural health monitoring (SHM) system, is its high cost, directly related to the cost of the instrumentation and in particular the number of sensors used. In this framework, dynamic approaches—mainly concerned with output-only techniques—have been successfully adopted to locate and quantify structural damages for historical [1,2] and recent construction [3,4]. Damage effects have been investigated, using non-classical continuum approaches, developed for materials with microstructure, by investigating displacement fields and wave propagation [12,13,14]
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