Work

Computer vision wireless sensors for displacement influence line/surface measurement of footbridges using stationary pedestrian loading

Year: 2025

Type: article

Abstract: Although using a heavy vehicle at a consistent speed is a common method to estimate displacement influence lines or displacement influence surfaces (DILs/DISs) of vehicular bridges, it requires algorithms to separate the dynamic and static components from measured displacements. This decomposition process can introduce uncertainties in the results. Additionally, employing vehicles is logistically impractical for most footbridges. To overcome these issues, this paper proposes a new, practical framework using computer vision to measure DILs/DISs on footbridges. It combines a stationary pedestrian loading strategy with a computer vision input–output wireless sensor network (CVIO-WSN). This framework has two main features: (1) pedestrians follow the “step-and-stand” rule, and their weight acts as a static load when they stand still at discrete locations across the footbridge for DIL/DIS measurement; (2) CVIO-WSN consists of input nodes for human load localization and output nodes for simultaneous structural response measurement, allowing load and response data to be collected in a contactless way that minimizes disruption to operational structures. Two laboratory experiments were conducted to validate this system. The first evaluated the timestamping accuracy between two identical sensor nodes tracking the same moving target, showing an average synchronization error of 2.39 ms. The second assessed the localization accuracy of the input nodes, with the average error of 14.0 mm on the X-axis and 16.9 mm on the Y-axis. The method was then applied to an experimental floor structure and an operational full-scale footbridge. In the first application, the input nodes tracked a human through a sequence of 77 locations across the floor, while the output node measured structural displacement at the center, successfully obtaining the structural DIS. In the second application, the method localized four humans (pedestrians) moving to discrete locations across an operational arch footbridge and briefly remaining stationary while measuring displacement at two points of the structure. Although the measurement results were promising, using heavier pedestrians or increasing their number is recommended to improve the signal-to-noise ratio of the structural displacement measurements.

Source: Computer-Aided Civil and Infrastructure Engineering

DOI: 10.1111/mice.70008