Data Management, Mining, and Inference for Bridge Monitoring

Pennsylvania Department of Transportation

Data Management, Mining, and Inference for Bridge Monitoring

Work Order (WO) 003

Dr. Piervincenzo Rizzo, Principal Investigator, pir3@pitt.edu, 412-624-9575

The overall scope of this project is to investigate advanced data management, analysis, mining and inference approaches for bridge health monitoring, safety evaluation, reliability and resilience assessment of instrumented bridges in Pennsylvania. The project consists of:

• Conducting a literature review of current or past bridge instrumentation for structural health monitoring (SHM) in the U.S.
• Examining the latest inspection reports of the ten bridges that are part of the PennDOT pilot bridge instrumentation program. The examination include the load test reports subsequent to the instrumentation of the bridge.
• Analyzing and processing the data streamed from the sensors and stored in the repository. The data were recorded during test-load events, representative service load events and, for an extensive period of time that can be up to 2 years.
• Creating finite element models of the bridge to compare the experimental values from the SHM system to the predicted models. The models are also used to simulate some damage scenarios in order to evaluate the effect of such damages on the bridges.
• Providing recommendations relative to the PennDOT bridge instrumentation program.