The focus of this project is to develop strategies for the integration of nondestructive evaluation (NDE) data from the RABITâ„˘ Bridge Deck Assessment Tool with structural performance data from from THMPERâ„˘ (Targeted Hits for Modal Parameter Estimation and Rating and Structural Health Monitoring) and to fuse the disparate data collected under the Federal Highway Administration’s (FHWA) Long-Term Bridge Performance (LTBP) Program. A broad range of approaches were considered that include both non-physics-based and physics-based modeling. Non-physics-based modeling refers to a class of fusion approaches that employ statistical and data mining tools to improve the reliability of data and its correlation with desired response indices or attributes. Physics-based modeling, on the other hand, makes use of the principles of physics (such as equilibrium, kinematics, diffusion etc.) to supplement field collected data to improve its reliability and facilitate its interpretation.
Deliverables for this project included a literature review of data fusion, data visualization, and data correlation techniques and a final report including detailed documentation and assessment of several different data fusion approaches, and recommendations related to both the most promising methods and future areas of research.