PROBABILITY ANALYSIS OF STRUCTURE DAMAGE IDENTIFICATION INCLUDING SYSTEM UNCERTAINTY

Because of many factors such as the discreteness of concrete materials and measured noise, the effects of uncertain parameters should be taken into consideration during the damage identification. This paper proposes a probability approach for the damage identification of structures considering uncertainties in structural parameters. The random parameter is assumed to follow Gaussian and non-Gaussian distribution. Based on the theoretical model and the statistical moment-sensitivity, the probabilistic structural models in undamaged and damaged states are obtained by two-stage model updating, and then the Probabilities of Damage Existence (PDE) of each element are calculated as the damage criterion and two-stage model updating. On the other hand, some improvement has been made to lessen the measured responses with segmentation time. The new stochastic damage detection method can not only locate structural damage but also identify damage severity. A ten-story shear building model subjected to ground motions and a simply supported beam with white noise are considered to demonstrate the proposed method.