Bridge Real-Time Damage Identification Method Using Inclination and Strain Measurements in the Presence of Temperature Variation

In this paper, a new real-time damage identification method has been presented for bridge structural health monitoring (SHM) considering temperature variation. The method utilizes model-based damage identification that involves three major steps: (1) efficient basis functionsextracted from finite-element (FE) models prior to real-time identification; (2) partial least-squares regression (PLSR) analyses; and (3) the fusion of different types of structural responses into damage indicator. By treating local damages as equivalent vertical loads and then cross-referencing global (inclinations) and local (strain) data, the hidden damage information in bridge structures can be detected and localized in a timely fashion, even in the presence of unknown temperature variation as well as vehicle loads. Inclinations alone cannot reflect local damages, but by fusing inclinations and strains (that represent local damage) into the proposed damage indicator, local damages can be identified. Numerical simulations on a medium-span continuous bridge demonstrate that the proposed method is insensitive to measurement noise and some common modeling errors, revealing the potential of real-time damage identification in bridge SHM applications.