Abstract

Information on dynamic displacement is an effective indicator for structures condition evaluation and provides a quantised insight into the structural analysis. This paper proposes a low-cost system based on computer vision using a smartphone to measure dynamic displacement, and then identify the dynamic properties of structures. Conventional sensors like linear variable differential transformers (LVDT), GPS, and accelerometer in monitoring systems have limitations of high price, inaccessibility, and accuracy. However, some new technologies eliminate these disadvantages. For example, a smartphone with a high-resolution camera becomes more affordable, which is regarded as appropriate equipment for structural health monitoring (SHM). Based on the optical flow, this method allows users to track points with a specific interval in the chosen region and reduces the displacement drift induced by the Kanade–Lucas–Tomasi (KLT) method. With the method applied, the region of interest is relocated according to pixel motion, and feature points are reselected. The accuracy of the system is verified on a laboratory suspension bridge model, and the results of modal frequency are confirmed with an accelerometer and FEM simulations.

摘要

动态位移信息是结构状态评估的有效指标，并提供对结构分析的量化洞察。本文提出了一种基于计算机视觉的低成本系统，使用智能手机测量动态位移，然后识别结构的动态特性。监控系统中的线性可变差动变压器 (LVDT)、GPS 和加速度计等传统传感器具有价格高、难以接近和准确性的局限性。然而，一些新技术消除了这些缺点。例如，配备高分辨率摄像头的智能手机变得更加实惠，被认为是结构健康监测 (SHM) 的合适设备。基于光流，该方法允许用户在所选区域内以特定间隔跟踪点，并减少由 Kanade-Lucas-Tomasi (KLT) 方法引起的位移漂移。应用该方法，根据像素运动重新定位感兴趣区域，并重新选择特征点。该系统的准确性在实验室悬索桥模型上得到验证，模态频率的结果通过加速度计和 FEM 模拟得到确认。