2134/10789
H.F. Lam
H.F.
Lam
Costas Papadimitriou
Costas
Papadimitriou
Evangelos Ntotsios
Evangelos
Ntotsios
Optimal experimental design for structural health monitoring applications
Loughborough University
2012
Structural identification
Experimental design
Information entropy
Sensor placement
Pareto optima
Built Environment and Design not elsewhere classified
2012-10-29 14:21:23
Conference contribution
https://repository.lboro.ac.uk/articles/conference_contribution/Optimal_experimental_design_for_structural_health_monitoring_applications/9429980
Successful structural health monitoring and condition assessment depends to a large extent
on the sensor and actuator networks place on the structure as well as the excitation characteristics. An optimal
experimental design methodology deals with the issue of optimizing the sensor and actuator network, as well
as the excitation characteristics, such that the resulting measured data are most informative for monitoring the
condition of the structure. Theoretical and computational issues arising in optimal experimental design are
addressed. The problem is formulated as a multi-objective optimization problem of finding the Pareto optimal
sensor configurations that simultaneously minimize appropriately defined information entropy indices related
to monitoring multiple probable damage scenarios. Asymptotic estimates for the information entropy, valid
for large number of measured data, are used to rigorously justify that the selection of the optimal experimental
design can be based solely on nominal structural models associated with the probable damage scenarios,
ignoring the details of the measured data that are not available in the experimental design stage. Heuristic algorithms
are proposed for constructing effective, in terms of accuracy and computational efficiency, sensor
configurations. The effectiveness of the proposed method is illustrated by designing the optimal sensor configurations
for monitoring damage on a shear model of a building structure.