Enriched Sensor Data for Enhanced Bridge Weigh-in-Motion (eBWIM) Applications

Principal Investigator(s):

Arturo Schultz, Former Professor, Civil, Environmental and Geo-Engineering


  • John Hourdos, Former Research Associate Professor, Civil, Environmental and Geo-Engineering

Project summary:

Bridge weigh-in-motion (BWIM) systems, which measure bridge deformation under live loading to estimate weights of passing vehicles, have been in development since Moses first introduced the concept in 1979. Despite advances made since its introduction, important limitations for BWIM systems still exist. A feasibility study was performed to determine if some of the limitations--including poor accuracy with multiple vehicle passage, either in tandem or side-by-side; and inability to accurately capture the passage of a vehicle moving at variable speeds--could be overcome by enriching the data set available to the BWIM system. Non-contact measurements collected in real time on the topside of the bridge can enrich the data set, and by taking advantage of these measurements, a more accurate and effective enriched bridge weigh-in-motion (eBWIM) system can be developed. Several sensing technologies were reviewed, including fiber Bragg gratings, MEMS accelerometers, microwave radar sensors, magnetic sensors, active infrared detectors, and video image vehicle detection systems. Preliminary results indicated that there was no clear candidate for a fully mature sensing system that would satisfy all the criteria in this study. However, microwave radar sensors have a reasonably low cost, are the least intrusive, and perform better in all weather conditions compared to the other sensors. A testbed using radar sensors has been proposed to investigate the accuracy of the eBWIM system. If the desired accuracy of the eBWIM system can be achieved, its implementations should prove to be invaluable for enforcing bridge weight limits, studying truck traffic patterns, and managing bridge inventories.

Project details:

  • Project number: 2017017
  • Start date: 05/2016
  • Project status: Completed
  • Research area: Infrastructure
  • Topics: Bridge design and sensing