An innovative technique to assess structural health just after subjected to impulsive loadings (blasts, explosions, etc.) underdevelopment at the University of Arizona was experimentally verified and is presented in this paper. The authors called it the Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. The system is represented by finite elements and a Kalman filter-based system identification (SI) technique is used to identify the system. Some of the major characteristics of the method are that it does not require information on input excitation and can identify a system with limited noise-contaminated response information measured at few node points. To implement the Kalman-filter based algorithm, the information on the input excitation and the initial state vector must be available. The authors proposed a two-stage approach. In the first stage, based on the limited measured response information available at the locations of the sensors, a substructure is identified. After the completion of the first stage, the input excitation information that caused the responses and the stiffness of all the elements in the substructure can be evaluated. Then, in stage 2, the Kalman-filter based algorithm is used to identify the whole structure. The experimental verification of the method is emphasized in this paper.
Health Assessment of Large Two Dimensional Structures Using Limited Information: Recent Advances
