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Target-free approach for vision-based structural system identification using consumer-grade cameras

机译:使用消费级相机进行基于视觉的结构系统识别的无目标方法

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Recent reports on America's infrastructure have emphasized the importance of structural health monitoring of civil infrastructures. System identification is a key component of many structural health monitoring strategies. Current system identification methods estimate models of a structure by measuring displacements, accelerations, and strains with wired or wireless sensors. However, these methods typically involve installation of a limited number of sensors at discrete locations and require additional data acquisition devices. To overcome these limitations, computer vision-based techniques have been introduced recently that employ high-speed and high-resolution cameras. Such cameras can be quite costly and require tedious installation of targets. This paper investigates the potential of using consumer-grade cameras for structural system identification without the need to install targets. The underlying methods for target-free displacement measurements are introduced, including region of interest selection, feature detection, point tracking, and outlier removal. A set of experiments are conducted to assess the efficacy of the proposed approach by comparing the accuracy of the identified model with one obtained using a conventional wired system. Careful comparison of the results demonstrates the significant potential of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.
机译:关于美国基础设施的最新报告强调了对民用基础设施进行结构健康监控的重要性。系统识别是许多结构健康监视策略的关键组成部分。当前的系统识别方法通过使用有线或无线传感器测量位移,加速度和应变来估计结构的模型。但是,这些方法通常涉及在离散位置安装有限数量的传感器,并且需要其他数据采集设备。为了克服这些限制,最近引入了基于计算机视觉的技术,该技术采用了高速和高分辨率的相机。这样的相机可能非常昂贵并且需要繁琐的目标安装。本文研究了使用消费级相机识别结构系统而无需安装目标的潜力。介绍了用于无目标位移测量的基本方法,包括感兴趣区域选择,特征检测,点跟踪和离群值去除。通过将识别出的模型的准确性与使用常规有线系统获得的模型进行比较,进行了一组实验,以评估所提出方法的有效性。仔细比较结果表明了该方法的巨大潜力。版权所有©2016 John Wiley&Sons,Ltd.

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