Structural-System Identification via a Reduced System and the Sensor-Location Selection Method

Abstract

The structural-vibration behavior of a plate model is expressed as a combination of the initial state behavior of the structure and its associated perturbations. The dynamic behavior obtained from a limited number of accessible nodes and their associated degrees of freedom is employed to detect structural changes that are consistent with the perturbations. The equilibrium model is described in terms of the measured and unmeasured modal data. Unmeasured information is estimated using an iterated improved reduction scheme. Because the identification problem depends on the measured information, the quality of the measured data determines the accuracy of the identified model and the convergence of the identification problem. The accuracy of the identification depends on the measurement/sensor location. In this study, a more accurate identification method using the optimal sensor-location selection method is proposed. Experimental examples are employed to examine the convergence and accuracy of the proposed method applied to an inverse problem of system identification.