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Identification of moving loads based on the information fusion of weigh-in-motion system and multiple camera machine vision

机译:基于动画系统信息融合的识别移动负载及多个相机机视觉

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摘要

Accurately identifying moving loads is of significance for the health monitoring of bridges. However, since the existing identification techniques can only realize load identification in one direction or for part of bridges, it is still a challenge to simultaneously identify transverse and longitudinal loads on the full deck of bridge. This paper proposed an information-fusion-based method for the load identification to be applied to bridges of different lengths. In this method, the pavement-based weigh-in-motion system (WIMs) laid out at the beginning of the bridge is used to obtain the weight of vehicles captured by cameras. The videos of traffic flow acquired by multiple cameras arranged along the bridge are employed to calculate the vehicle's trajectory and location. The weight and location data are matched when the vehicle in the video crosses the piezoelectric sensor of WIMs for the same time as the WIMs records a weight information. Further, since the vehicles are equivalent to concentrated loads, values and locations of all moving loads on the whole bridge are identified in real time. The reliability and accuracy of the proposed approach is verified by multi-view 3D simulation video data and the field data from a ramp bridge. (C) 2019 Elsevier Ltd. All rights reserved.
机译:准确识别移动负载对于桥梁的健康监测具有重要意义。然而,由于现有的识别技术只能在一个方向上或一部分桥梁中实现负载识别,因此同时识别桥上的全甲板上的横向和纵向负载仍然是一项挑战。本文提出了一种基于信息融合的方法,用于将载荷识别应用于不同长度的桥梁。在该方法中,用于在桥的开头布置的基于路面的重入体系(Wims)来获得由摄像机捕获的车辆的重量。采用由沿桥梁布置的多个相机获取的交通流量的视频来计算车辆的轨迹和位置。当VIMS记录重量信息时,当视频中的车辆交叉WIM的压电传感器时,重量和位置数据匹配。此外,由于车辆等同于集中载荷,因此整个桥上的所有移动载荷的值和位置实时识别。通过来自斜坡桥的多视图3D模拟视频数据和现场数据来验证所提出的方法的可靠性和准确性。 (c)2019年elestvier有限公司保留所有权利。

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