A novel health assessment technique with minimum information

A novel structural health assessment method is proposed for detecting defects at the element level using only minimum measured response information considering imperfect mathematical model representing the structure, various sources of uncertainty in the mathematical model, and uncertainty in the measured response information. It is a linear time domain finite element-based system identification procedure capable of detecting defects at the local element level using only limited response measurements and without using any information on the exciting dynamic forces. The technique is a combination of the modified iterative least-squares technique with unknown input excitation (MILS-UI) proposed earlier by the research team at the University of Arizona and the extended Kalman filter with a weighted global iteration (EKF-WGI) procedures to address different sources of uncertainty in the problem. The authors denote the new method as GILS-EKF-UI To implement the concept, a two-stage substructure approach is used. In the first stage, a substructure is selected that satisfies all the requirements for the MILS-UI procedure. This provides information on the initial state vector and the input excitation required to implement any EKF-based procedure. In the second stage, the EKF-WGI is applied to identify the whole structure. This way the whole structure, defect free or defective, can be identified with limited response measurements in the presence of uncertainty and without using excitation information. The theoretical concept behind this novel method is presented in this paper. Copyright (C) 2007 John Wiley & Sons, Ltd.