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A platform for research: civil engineering, architecture and urbanism
Research on Construction of Digital Twin System for Bridge Vehicle Load Identification
In order to improve the intelligent level of bridge operation and maintenance, breaking through the bottleneck of real-time positioning of moving vehicle load on bridge deck, This research combines image recognition, target tracking, data fusion and other technologies, a digital twin system for real-time identification of vehicle load position on bridge deck is developed. Firstly, the virtual bridge vehicle operation platform is developed, the multi-angle, multi-environment and multi-type vehicle data sets are obtained; Secondly, A bridge global image information fusion technology based on vision stitching is proposed, combined with the improved deep learning algorithm, the real-time recognition and tracking of vehicles in the whole bridge are realized; Furthermore, integrated bridge camera real-time image data and bridge dynamic weighing system, a digital twin system for real-time identification of vehicle load position on bridge deck is constructed; Finally, the above system is applied to Baijusi Yangtze River Bridge, realized the real-time identification of vehicles and vehicle load positions of Baijusi Yangtze River Bridge.
Research on Construction of Digital Twin System for Bridge Vehicle Load Identification
In order to improve the intelligent level of bridge operation and maintenance, breaking through the bottleneck of real-time positioning of moving vehicle load on bridge deck, This research combines image recognition, target tracking, data fusion and other technologies, a digital twin system for real-time identification of vehicle load position on bridge deck is developed. Firstly, the virtual bridge vehicle operation platform is developed, the multi-angle, multi-environment and multi-type vehicle data sets are obtained; Secondly, A bridge global image information fusion technology based on vision stitching is proposed, combined with the improved deep learning algorithm, the real-time recognition and tracking of vehicles in the whole bridge are realized; Furthermore, integrated bridge camera real-time image data and bridge dynamic weighing system, a digital twin system for real-time identification of vehicle load position on bridge deck is constructed; Finally, the above system is applied to Baijusi Yangtze River Bridge, realized the real-time identification of vehicles and vehicle load positions of Baijusi Yangtze River Bridge.
Research on Construction of Digital Twin System for Bridge Vehicle Load Identification
Xue, Xiankai (author) / Zhu, Hao (author) / Chen, Yuan (author) / Wang, Yongwei (author)
2022-11-25
4703199 byte
Conference paper
Electronic Resource
English
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