FINITE ELEMENT MODEL UPDATING

Abstract

Detection of damage in a structural system is an important part of structural health monitoring. Damage in a structure alters its dynamic characteristics. This alteration is characterized by changes in the modal parameters, i.e., modal frequencies, modal damping values and mode shapes associated with each modal frequency. Over the past few years, many damage detection methods have been developed which are based on comparing the results of an analytical model with the test results of a damaged structure. However these methods are computationally intensive and require a Finite Element (FE) model, which is carefully refined with test data of an undamaged structure. The development of such models requires matching the mode of vibration identified from the test data and from the analytical FE model. This is subjected to uncertainties if the number or position of transducer is inadequate, also it becomes ambiguous, when the modes are not well separated and the measurement data is masked by noise. The present study is attributed to detection of damage in a complex framed structure designed on strong column weak beam concept. First modal identification of a linear structural frame is carried out in order capture the undamaged state of structure. This is done by adopting Bayesian Time Domain Approach subject to conditions where (1) the measured data is corrupted with noise (2) measured data is available at only a few degrees of freedom (DOF) and (3) a few fundamental modes are identified. Then the same approach is used to identify the damage in the structure. This is done by breaking the measured data from the damaged structure in to chunks and simulating online monitoring, wherein, the modal parameters are identified for each chunk, and the modal parameters are monitored to identify the presence of damage in the structure