A methodology is presented for designing cost-effective optimal sensor configurations for structural model updating and health monitoring purposes. The optimal sensor configurations ration is selected such that the resulting measured data are most informative about the condition of the structure. This selection is based on an information entropy measure of the uncertainty, in the model parameter estimates obtained using a statistical system identification method. The methodology is developed for the uncertain excitation case, encountered in practical applications for which data are to be taken either from ambient, vibration tests or from other uncertain excitations such as earthquake and wind. Important issues related to robustness of the o...
The focus of this study is on the selection of ideal sensor location through computational and hypot...
The number of sensors and the corresponding locations are very important for the success of structur...
The paper investigates the role of model errors and parametric uncertainties in optimal or near opti...
A methodology is presented for designing cost-effective optimal sensor configurations for structural...
A methodology is presented for designing cost-effective optimal sensor and actuator configurations u...
Computational and theoretical issues in selection of optimal sensor configuration are addressed in t...
Theoretical and computational issues arising in the selection of the optimal sensor configuration fo...
A statistical methodology is presented for optimally locating the sensors in a structure for the pur...
Optimal sensor configuration for a nine-storey shear building model is presented using statistical m...
This project focuses on select optimal sensor configuration placement by computational and theoretic...
Theoretical and computational issues arising in the selection of the optimal sensor configuration in...
Theoretical and computational issues arising in the selection of the optimal sensor configuration in...
Successful structural health monitoring and condition assessment depends to a large extent on the se...
A statistical methodology is presented for optimally locating the sensors in a structure for the pu...
A statistical methodology is presented for optimally locating the sensors in a structure for the pur...
The focus of this study is on the selection of ideal sensor location through computational and hypot...
The number of sensors and the corresponding locations are very important for the success of structur...
The paper investigates the role of model errors and parametric uncertainties in optimal or near opti...
A methodology is presented for designing cost-effective optimal sensor configurations for structural...
A methodology is presented for designing cost-effective optimal sensor and actuator configurations u...
Computational and theoretical issues in selection of optimal sensor configuration are addressed in t...
Theoretical and computational issues arising in the selection of the optimal sensor configuration fo...
A statistical methodology is presented for optimally locating the sensors in a structure for the pur...
Optimal sensor configuration for a nine-storey shear building model is presented using statistical m...
This project focuses on select optimal sensor configuration placement by computational and theoretic...
Theoretical and computational issues arising in the selection of the optimal sensor configuration in...
Theoretical and computational issues arising in the selection of the optimal sensor configuration in...
Successful structural health monitoring and condition assessment depends to a large extent on the se...
A statistical methodology is presented for optimally locating the sensors in a structure for the pu...
A statistical methodology is presented for optimally locating the sensors in a structure for the pur...
The focus of this study is on the selection of ideal sensor location through computational and hypot...
The number of sensors and the corresponding locations are very important for the success of structur...
The paper investigates the role of model errors and parametric uncertainties in optimal or near opti...