SYSTEM-IDENTIFICATION WITH LIMITED OBSERVATIONS AND WITHOUT INPUT

A time domain system identification technique is proposed to estimate the stiffness and damping parameters, at the element level, of a struc ture excited by unknown or unmeasured input forces. The unknown input forces could be of any type, including seismic loading. The unique fea ture of this technique is that it does not require response measuremen ts at all dynamic degrees of freedom of the structure. This new proced ure is a combination of an iterative least-squares procedure with unkn own input excitations (ILS-UI) proposed earlier by the writers, and th e extended Kalman filter method with a weighted global iteration (KF-W GI). The new procedure is denoted by the writers as ILS-EKF-UI. The un certainty in the output responses is considered, and its effect on the accuracy of the identified parameters is analyzed. The efficiency, ac curacy, and robustness of the proposed algorithm are illustrated by nu merical examples. The accuracy of the proposed ILS-EKF-IU procedure is of the same order as that of ILS-UI; however, it requires a longer re sponse measurement. This is expected, since ILS-EKF-UI identifies a st ructure using less information than the ILS-UI does. However, the effi ciency of the new algorithm can be improved by considering a shorter d uration of response measurements for the ILS-UI procedure and a longer duration for the KF-WGI without compromising the accuracy of the iden tified parameters.