Bridge damage assessment by AI and static measurements

Detection, localization and quantification of structural damage and the subsequent development of a maintenance plan is a challenging task for structural engineers and infrastructure owners. Both genetic algorithms and influence lines or surfaces can be suitable for structural damage assessment. In this contribution, a genetic algorithm, based on static properties, and displacement influence lines are combined for estimating location and severity of hypothesized damage scenarios in a girder bridge. A simply supported, prestressed concrete railway bridge, located in the northern Italy, was selected as a benchmark. The implemented algorithm solves the inverse problem for estimating damage location and severity based on static deflections and rotations measured at few points. The results look promising and encourage further developments.