Study on hybrid model combining super learner and physic-based models for SHM in bridges using low-cost BWIM

Many structural health monitoring (SHM) techniques have been devised over the past decades. However, there is no one-size-fits-all solution that can be applied to all bridges for structural assessments. Bridge-based weight-in-motion systems (BWIM) use the structure’s response to estimate vehicles’ load distribution. This technology is primarily used to obtain vehicle axle weights efficiently in public. BWIM can be a candidate that overcomes the shortfall of SHM. The use of BWIM systems for SHM has rarely been investigated. The objectives are (1) to study and deploy low-cost BWIM sensors for accurate SHM, (2) to evaluate the S-BWIM system, and (3) assessment of the hybrid model capacity combining physics-based mathematical models (PSM) and practical machine-learning (ML) models. A new low-cost BWIM system verified with numerical results will be installed in the local area, Dallas, and Fort Worth (DFW). This study will help Region 6 communities, where low-cost measurements are already used, and prediction models are publicly available for monitoring both traffic loads and bridge conditions. The development of a hybrid model generally adaptable for various conditions of bridges will be a major contribution to the research community. A comparative study of the proposed machine learning algorithm (super learner) with low-cost BWIM sensors will also be implemented in Region 6.


  • English


  • Status: Completed
  • Funding: $ 122000
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Transportation Consortium of South-Central States (Tran-SET)

    Louisiana State University
    Baton Rouge, LA  United States  70803
  • Project Managers:

    Mousa, Momen

  • Performing Organizations:

    University of Texas at Arlington

    Department of Civil Engineering
    Box 19308
    Arlington, TX  United States  76019
  • Principal Investigators:

    Ham, Suyun

  • Start Date: 20200801
  • Expected Completion Date: 20220201
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01757534
  • Record Type: Research project
  • Source Agency: Transportation Consortium of South-Central States (Tran-SET)
  • Contract Numbers: 69A3551747106
  • Files: UTC, RIP
  • Created Date: Nov 10 2020 8:35PM