Abstract
Resilience is about improved operational performance and safety by ensuring integrity and redundancy of infrastructure systems. Structural health monitoring (SHM) of old infrastructure like bridges is crucial to ensuring resilience. The fusion of affordable vision-based structural health monitoring (VBSHM) systems with effective damage detection techniques has the potential to provide cost-effective solutions to support condition assessments of such old bridges, - a necessary step towards ensuring their safety and consequently resilience. With VBSHM, distributed sensing along a bridge is attainable, after which image-processing can be used to obtain bridge response. One of such responses is curvature. The curvature technique involves fitting a curve to response from tracked targets, extracting their quadratic coefficients across all loading timesteps, and taking the maximum coefficient as bridge response. Feasibility of this technique is demonstrated on a numerical model of a truck-loaded bridge girder subjected to multiple damage scenarios. Noise is also added to replicate real-world scenarios. Damages can be detected and localised but are influenced by damage extent and measurement noise. The technique shows potential for field applications.
Original language | English |
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Pages | 120-123 |
Number of pages | 4 |
Publication status | Published - 2020 |
Event | Joint International Resilience Conference, JIRC 2020: Interconnected: Resilience Innovations for Sustainable Development Goals - Online conference Duration: 23 Nov 2020 → 27 Nov 2020 |
Conference
Conference | Joint International Resilience Conference, JIRC 2020 |
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Abbreviated title | JIRC |
Period | 23/11/20 → 27/11/20 |