Bridge Damage Detection Approach Using a Roving Camera Technique

Abstract

Increasing extreme climate events, intensifying traffic patterns and long-term underinvestment have led to the escalated deterioration of bridges within our road and rail transport networks. Structural Health Monitoring (SHM) systems provide a means of objectively capturing and quantifying deterioration under operational conditions. Computer vision technology has gained considerable attention in the field of SHM due to its ability to obtain displacement data using non-contact methods at long distances. Additionally, it provides a low cost, rapid instrumentation solution with low interference to the normal operation of structures. However, even in the case of a medium span bridge, the need for many cameras to capture the global response can be cost-prohibitive. This research proposes a roving camera technique to capture a complete derivation of the response of a laboratory model bridge under live loading, in order to identify bridge damage. Displacement is identified as a suitable damage indicator, and two methods are used to assess the magnitude of the change in global displacement under changing boundary conditions in the laboratory bridge model. From this study, it is established that either approach could detect damage in the simulation model, providing an SHM solution that negates the requirement for complex sensor installations.

Vision-Based Damage Detection Using Inclination Angles and Curvature

“…Damage threshold should be selected based on the level of measurement noise. If measurements are less noisy, it can be set to 5% [24,21]. If we use 5% here, a lot more areas will be captured, which makes damage localization a bit more difficult.…”

Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring

“…Results show that, although bridge response can be measured accurately, traffic and deformation monitoring cameras need to be synchronized and much more data (many more cyclist crossing) obtained to generate an accurate bridge signature and implement the proposed bridge response characterization approach. Alternatively a roving camera technique, in which one camera is set as a reference camera while locations of other cameras are changed, can be considered [20]. This technique also required the load and its application to be kept consistent.…”

CCTV Camera Array for the Displacement and Strain Measurement of a Beam Specimen in a Laboratory

“…The phase obtained by Equation ( 2) is wrapped by 2π and lies between −π and π, which creates discontinuous deformation while calculating. Thus, a phase unwrapping algorithm must be combed by a local phase unwrapping algorithm to ensure accuracy in the measurement of strain distribution [22]. Phase 𝜙 of the moiré fringe is the subtraction of phase 𝜙 of the reference grating from phase 𝜙ϕ of the specimen grating, such that:…”

“…Further, in terms of experiments, comparative experiments conducted in a columnar cantilever beam connected to a loading jack and laser displacement meter demonstrated the effectiveness of the method for deformation measurement when the errors between the measurements were compared [14,21]. Different cameras were used for the damage detection of bridges under different loading conditions [22][23][24][25][26][27][28][29].…”