Sensor Placement for Parameter Estimation of Structures using Fisher Information Matrix

A method based on Fisher Information from sensitivity matrix is presented for sensor placement in nondestructive tests used for parameter estimation and structural model updating using sparse and noisy measurements. This method can be used for both static and modal nondestructive tests but in this paper sensor placement for only the static nondestructive data is presented. An error function that represents the difference between analytical and measured data is used in this research. This method ranks the sensor locations and load cases using the sensitivity matrix that represents the rate of change of the error function used with respect to each unknown stiffness parameter. The proposed method is applied to a single story frame to demonstrate the selection of strategic sensor locations. This example shows that this is an effective and robust method for strategic sensor placement with regard to the stiffness parameters to be estimated. Introduction The efficiency of the nation's transportation system depends to a large extent on health monitoring and maintenance of bridges and other transportation systems. There is an increasing need for testing and monitoring of the in-service behavior and integrity of key structures such as bridges, tall buildings transmission towers, aircrafts, satellites, etc. Both static and dynamic nondestructive test data can be used to determine the unknown properties such as axial, bending, torsional rigidities of beams, and foundation stiffness using parameter estimation methods. Parameter estimation methods that are finite element based are often sensitive to the sensor locations and measurement noise. Selection of measurement locations and accuracy 1 Professor, Dept. of Civil and Environmental Engineering, Tufts University, Medford, MA 02155. Phone: (617) 627-3211 email: [email protected] 2 Ph. D. Candidate, Dept. of Civil and Environmental Engineering, Tufts University, Medford MA 02155. Phone:(617) 627-5185 email: [email protected]