Application of the on-line recursive least-squares method to perform structural damage assessment

The identification of structural damage is an important objective of health monitoring for civil infrastructure. An on-line recursive least-squares (RLS) identification technique is applied in this study to identify the time-varying dynamic parameters of structures subjected to earthquake loadings. Based on the framework of adaptive filters, the observations are obtained sequentially in real time. It is desirable to perform the identification tasks recursively to save computation time and to be able to observe the variations of parameters on-line. Computation of the classical least-squares (LS) method can be arranged recursively so that the estimated parameters at previous step can be used to predict the responses at current time. The one-step ahead predicted error between estimated response and measured response is calculated by the on-line RLS method and the dynamic properties of system can be identified as well. The purpose of this study is to apply the RLS method to verify the identification procedures and to perform the damage assessment on a three-floor shaking table benchmark model tested at NCREE in Taiwan. Furthermore, both classical LS and RLS methods are implemented to investigate the recorded strong-motion data of Tai-Tung Fire Bureau Building located at Tai-Tung City in Taiwan, which had been demolished due to severe damage after a magnitude 6.2 earthquake in 2006. By observing the variations of the identified time-varying modal properties of both benchmark model and real building, global damage behavior due to weak element or failure of components can be revealed.