A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Structural Identification Using Computer Vision–Based Bridge Health Monitoring
This paper presents a new structural identification (St-Id) framework along with a damage indicator, displacement unit influence surface using computer vision–based measurements for bridge health monitoring. Unit influence surface (UIS) of a certain response (e.g., displacement, strain) at a measurement location on a beam-type or plate-type structure (e.g., single-span or multispan bridge with its deck) is defined as a response function of the unit load with respect to the any given location of the unit load on that structure. The novel aspect of this paper is a framework integrating vehicle load (input) modeling using computer vision and the development of a new damage indicator, UIS, using image-based structural identification. This framework is demonstrated on the large-scale bridge model in the University of Central Florida Structures Laboratory for verification and validation. The UIS damage indicators successfully identified the simulated damage on the bridge model, including damage detection and damage localization.
Structural Identification Using Computer Vision–Based Bridge Health Monitoring
This paper presents a new structural identification (St-Id) framework along with a damage indicator, displacement unit influence surface using computer vision–based measurements for bridge health monitoring. Unit influence surface (UIS) of a certain response (e.g., displacement, strain) at a measurement location on a beam-type or plate-type structure (e.g., single-span or multispan bridge with its deck) is defined as a response function of the unit load with respect to the any given location of the unit load on that structure. The novel aspect of this paper is a framework integrating vehicle load (input) modeling using computer vision and the development of a new damage indicator, UIS, using image-based structural identification. This framework is demonstrated on the large-scale bridge model in the University of Central Florida Structures Laboratory for verification and validation. The UIS damage indicators successfully identified the simulated damage on the bridge model, including damage detection and damage localization.
Structural Identification Using Computer Vision–Based Bridge Health Monitoring
Khuc, Tung (author) / Catbas, F. Necati (author)
2017-11-28
Article (Journal)
Electronic Resource
Unknown
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