Choi Insub, Kim JunHee, Kim Donghyun
Department of Architectural Engineering, Yonsei University, 50 Yonseiro, Seodaemun-gu, Seoul 120-749, Korea.
Sensors (Basel). 2016 Dec 8;16(12):2085. doi: 10.3390/s16122085.
Existing vision-based displacement sensors (VDSs) extract displacement data through changes in the movement of a target that is identified within the image using natural or artificial structure markers. A target-less vision-based displacement sensor (hereafter called "TVDS") is proposed. It can extract displacement data without targets, which then serve as feature points in the image of the structure. The TVDS can extract and track the feature points without the target in the image through image convex hull optimization, which is done to adjust the threshold values and to optimize them so that they can have the same convex hull in every image frame and so that the center of the convex hull is the feature point. In addition, the pixel coordinates of the feature point can be converted to physical coordinates through a scaling factor map calculated based on the distance, angle, and focal length between the camera and target. The accuracy of the proposed scaling factor map was verified through an experiment in which the diameter of a circular marker was estimated. A white-noise excitation test was conducted, and the reliability of the displacement data obtained from the TVDS was analyzed by comparing the displacement data of the structure measured with a laser displacement sensor (LDS). The dynamic characteristics of the structure, such as the mode shape and natural frequency, were extracted using the obtained displacement data, and were compared with the numerical analysis results. TVDS yielded highly reliable displacement data and highly accurate dynamic characteristics, such as the natural frequency and mode shape of the structure. As the proposed TVDS can easily extract the displacement data even without artificial or natural markers, it has the advantage of extracting displacement data from any portion of the structure in the image.
现有的基于视觉的位移传感器(VDS)通过使用自然或人工结构标记在图像中识别的目标运动变化来提取位移数据。本文提出了一种无目标的基于视觉的位移传感器(以下简称“TVDS”)。它可以在没有目标的情况下提取位移数据,这些数据随后作为结构图像中的特征点。TVDS可以通过图像凸包优化在图像中无目标地提取和跟踪特征点,即调整阈值并对其进行优化,以使它们在每个图像帧中具有相同的凸包,并且凸包的中心为特征点。此外,特征点的像素坐标可以通过基于相机与目标之间的距离、角度和焦距计算出的比例因子图转换为物理坐标。通过估计圆形标记直径的实验验证了所提出的比例因子图的准确性。进行了白噪声激励测试,并通过比较用激光位移传感器(LDS)测量的结构位移数据来分析从TVDS获得的位移数据的可靠性。利用获得的位移数据提取结构的动态特性,如振型和固有频率,并与数值分析结果进行比较。TVDS产生了高度可靠的位移数据以及高度准确的动态特性,如结构的固有频率和振型。由于所提出的TVDS即使在没有人工或自然标记的情况下也能轻松提取位移数据,它具有从图像中结构的任何部分提取位移数据的优势。