Project 3.08: Bridge Modal Identification via Video Processing and Quantification ofUncertainties

Bridge Modal Identification via Video Processing and Quantification of Uncertainties

Project 3.8

Project Summary

Bridges form a critical category of the U.S. transportation infrastructure, yet the current structural condition is only evaluated at “C+” according to the 2017 ASCE Infrastructure Report Card. In addition to the fact that 9.1% of the bridges in U.S. are structurally deficient, the bridges in New England are especially experiencing the burden of busy traffic and harsh wintery weather. There is a variety of factors that may affect the bridge dynamics and deteriorate the structures, such as creeping, corrosion, cyclic thermal loadings and accidental damages, and identification modal properties provides a global evaluation capability with rich physical meaning. However, this complicated scenario brings up the demanding in conducting the heterogeneous data acquisition and in-situ modal analysis, as well as quantifying the enormous amount of uncertainties that may come across. The problem we are trying to solve is to adopt portable video cameras and by processing the acquired videos, bridge dynamic systems, especially full-field mode shapes will be extracted to enhance the status awareness. The challenges exist while dealing with the rapidly changing environments and traffics, so that the statistical modeling is needed when interpreting the extracted information.

Principal Investigator

Dr. Zhu Mao


University of Massachusetts Lowell

Project Status


Project Cost


Start Date


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Office of the Assistant Secretary for Research and Technology, University Transportation Centers Program, Department of Transportation

Implementation of Research Outcomes:

No reported implementation prior to project end.

Impacts and Benefits of Implementation:

No reported impacts and benefits prior to project end.

Printable Project Information Sheet

March 2019 Semi-Annual Progress Report

June 2019 Bi-Monthly Progress Report

July 2019 Bi-Monthly Progress Report

September 2019 Semi-Annual Progress Report

January 2020 Quarterly Progress Report

March 2020 Quarterly Progress Report

June 2020 Quarterly Progress Report

September 2020 Quarterly Progress Report

December 2020 Quarterly Progress Report

March 2021 Quarterly Progress Report

June 2021 Quarterly Progress Report

October 2021 Quarterly Progress Report