Bayesian probabilistic damage detection of a reinforced-concrete bridge column

A Bayesian probabilistic approach for damage detection has been proposed fo r the continuous monitoring of civil structures (Sohn H, Law KH. Bayesian p robabilistic approach for structure damage detection. Earthquake Engineerin g and Structural Dynamics 1997; 26: 1259-1281). This paper describes the ap plication of the Bayesian approach to predict the location of plastic hinge deformation using the experimental data obtained from the vibration tests of a reinforced-concrete bridge column. The column was statically pushed in crementally with lateral displacements until a plastic hinge is fully forme d at the bottom portion of the column. Vibration tests were performed at di fferent damage stages. The proposed damage detection method was able to loc ate the damaged region using a simplified analytical model and the modal pa rameters estimated from the vibration tests, although (1) only the first be nding and first torsional modes were estimated from the experimental test d ata, (2) the locations where the accelerations were measured did not coinci de with the degrees of freedom of the analytical model, and (3) there exist ed discrepancies between the undamaged test structure and the analytical mo del. The Bayesian framework was able to systematically update the damage pr obabilities when new test data became available. Better diagnosis was obtai ned by employing multiple data sets than just by using each test data set s eparately. Copyright (C) 2000 John Wiley & Sons, Ltd.