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A novel computer vision-based monitoring methodology for vehicle-induced aerodynamic load on noise barrier

机译:一种基于计算机视觉的新型监测方法,用于车辆在隔音屏障上产生的空气动力负荷

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摘要

Due to the absence of antifatigue design under vehicle-induced aerodynamic load (VIAL) during the process of structural design, structural failures of noise barriers erected on urban highway viaducts have become a common issue in China. In this paper, a novel VIAL monitoring methodology is proposed, which can achieve a remote VIAL measuring only by analysis and application of the data from a traffic-monitoring camera. To establish this methodology, a VIAL determinative model and a computer vision system for measuring the vehicle running characteristics are developed. The accuracy and reliability of this methodology have been validated by a field experiment. By comparing with the results of vehicle-induced aerodynamic pressure (VIAP) from a sensor-based wind pressure acquisition system, it was found that the systemic root mean square deviations of maximum and minimum values of VIAP were 12.13% and 10.10%, respectively.
机译:由于在结构设计过程中缺乏在车辆气动载荷(VIAL)下的抗疲劳设计,在城市公路高架桥上竖立的隔音屏障的结构失效已成为中国的普遍问题。本文提出了一种新颖的VIAL监视方法,该方法仅通过对交通监控摄像机的数据进行分析和应用即可实现远程VIAL测量。为了建立这种方法,开发了用于测量车辆行驶特性的VIAL确定性模型和计算机视觉系统。该方法的准确性和可靠性已通过现场实验验证。通过与基于传感器的风压采集系统的车辆空气动力压力(VIAP)结果进行比较,发现VIAP最大值和最小值的系统均方根偏差分别为12.13%和10.10%。

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