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A Stand-Alone Smart Camera System for Online Post-Earthquake Building Safety Assessment

机译:在线地震后建筑安全评估的独立智能摄像头系统

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摘要

Computer vision-based approaches are very useful for dynamic displacement measurement, damage detection, and structural health monitoring. However, for the application using a large number of existing cameras in buildings, the computational cost of videos from dozens of cameras using a centralized computer becomes a huge burden. Moreover, when a manual process is required for processing the videos, prompt safety assessment of tens of thousands of buildings after a catastrophic earthquake striking a megacity becomes very challenging. Therefore, a decentralized and fully automatic computer vision-based approach for prompt building safety assessment and decision-making is desired for practical applications. In this study, a prototype of a novel stand-alone smart camera system for measuring interstory drifts was developed. The proposed system is composed of a single camera, a single-board computer, and two accelerometers with a microcontroller unit. The system is capable of compensating for rotational effects of the camera during earthquake excitations. Furthermore, by fusing the camera-based interstory drifts with the accelerometer-based ones, the interstory drifts can be measured accurately even when residual interstory drifts exist. Algorithms used to compensate for the camera’s rotational effects, algorithms used to track the movement of three targets within three regions of interest, artificial neural networks used to convert the interstory drifts to engineering units, and some necessary signal processing algorithms, including interpolation, cross-correlation, and filtering algorithms, were embedded in the smart camera system. As a result, online processing of the video data and acceleration data using decentralized computational resources is achieved in each individual smart camera system to obtain interstory drifts. Using the maximum interstory drifts measured during an earthquake, the safety of a building can be assessed right after the earthquake excitation. We validated the feasibility of the prototype of the proposed smart camera system through the use of large-scale shaking table tests of a steel building. The results show that the proposed smart camera system had very promising results in terms of assessing the safety of steel building specimens after earthquake excitations.
机译:基于计算机视觉的方法对于动态位移测量,损伤检测和结构健康监测非常有用。然而,对于在建筑物中使用大量现有摄像机的应用,使用集中式计算机的来自数十个摄像机的视频的计算成本成为巨大的负担。此外,当需要手动处理视频时,在特大地震袭击后,对成千上万栋建筑物进行迅速安全评估变得非常困难。因此,实际应用中需要一种基于分散式和全自动计算机视觉的方法来快速进行建筑物安全评估和决策。在这项研究中,开发了一种用于测量层间漂移的新型独立智能相机系统的原型。拟议的系统由一个摄像头,一个单板计算机和两个带微控制器单元的加速度计组成。该系统能够补偿地震激发期间摄像机的旋转影响。此外,通过将基于摄像机的层间漂移与基于加速度计的层间漂移融合,即使存在残留的层间漂移,也可以准确地测量层间漂移。用于补偿相机旋转效果的算法,用于跟踪三个感兴趣区域内三个目标运动的算法,用于将层间漂移转换为工程单位的人工神经网络,以及一些必要的信号处理算法,包括插值,交叉相关性和过滤算法已嵌入到智能相机系统中。结果,在每个单独的智能相机系统中实现了使用分散的计算资源的视频数据和加速度数据的在线处理,以获得层间漂移。使用地震过程中测得的最大层间位移,可以在地震激发后立即评估建筑物的安全性。通过使用钢结构建筑物的大型振动台测试,我们验证了所建议的智能相机系统原型的可行性。结果表明,提出的智能相机系统在评估地震激发后的钢结构标本的安全性方面具有非常可观的结果。

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