Optimization algorithms for system integration
This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising in structural dynamics and related to (1) model parameter estimation used for finite element model updating, (2) model-based damage detection in structures and (3) optimal sensor location for parameter estimation and damage detection. These problems are formulated as single- and multi-objective optimization problems of continuous or discrete-valued variables. Gradient-based, evolutionary, hybrid and heuristic algorithms are presented that effectively address issues related to the estimation of multiple local/global solutions and computational complexity arising in single and multi-objective optimization involving continuous and discrete variables. © 2008 Trans Tech Publications, Switzerland.
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Lam, H. F.; Papadimitriou, C.; Ntotsios, E. (2008)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 ...
Papadioti, D. C.; Papadimitriou, C. (2011)Finite element (FE) model updating and validation techniques are formulated as single and multi-objective optimization problems. A multi-objective optimization framework results in multiple Pareto optimal models that are ...
Ntotsios, E.; Christodoulou, K.; Papadimitriou, C. (2006)Theoretical and computational issues arising in the selection of the optimal sensor configuration in structural dynamics are addressed. The information entropy is introduced to measure the performance of a sensor configuration. ...