Robust optimal sensor configuration using the value of information

Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for...

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Bibliographic Details
Published in:Structural control and health monitoring 2022-12, Vol.29 (12), p.n/a
Main Authors: Cantero‐Chinchilla, Sergio, Papadimitriou, Costas, Chiachío, Juan, Chiachío, Manuel, Koumoutsakos, Petros, Fabro, Adriano T., Chronopoulos, Dimitrios
Format: Article
Language:English
Subjects:
Algorithms
Aluminum
Configurations
Cost benefit analysis
Diagnostic systems
Expected values
guided waves
Mathematical models
Metal plates
Methodology
Objective function
optimal sensor configuration
Optimization
Parameter uncertainty
Placement
prediction model error
robust optimization
Robustness
Sensors
Structural health monitoring
Structure-function relationships
value of information
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Summary:Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for (1) uncertainties from updatable and nonupdatable parameters, (2) variability of the objective function with respect to nonupdatable parameters, and (3) the spatial correlation between sensors. The optimal sensor configuration is obtained by maximizing the expected value of information, which leads to a cost‐benefit analysis that entails model parameter uncertainties. The proposed methodology is demonstrated on an application of structural health monitoring in plate‐like structures using ultrasonic guided waves. We show that accounting for uncertainties is critical for an accurate diagnosis of damage. Furthermore, we provide critical assessment of the role of both the effect of modeling and measurement uncertainties and the optimization algorithm on the resulting sensor placement. The results on the health monitoring of an aluminum plate indicate the effectiveness and efficiency of the proposed methodology in discovering optimal sensor configurations.
ISSN:1545-2255
1545-2263
DOI:10.1002/stc.3143