Optimal Sensors Placement in Dynamic Damage Detection of Beams Using a Statistical Approach

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 r...

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Bibliographic Details
Published in:Journal of optimization theory and applications 2020-12, Vol.187 (3), p.758-775
Main Authors: Lofrano, Egidio, Pingaro, Marco, Trovalusci, Patrizia, Paolone, Achille
Format: Article
Language:English
Subjects:
Applications of Mathematics
Asymptotic methods
Calculus of Variations and Optimal Control
Optimization
Damage detection
Damage localization
Dynamic response
Engineering
Error analysis
Error functions
Evaluation
Mathematics
Mathematics and Statistics
Monitoring
Operations Research/Decision Theory
Optimization
Parameters
Perturbation
Sensors
Statistical analysis
Structural damage
Theory of Computation
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Summary: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.
ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-020-01761-3