Lee Junhwa, Lee Kyoung-Chan, Cho Soojin, Sim Sung-Han
School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea.
Korea Railroad Research Institute, Uiwang 16105, Korea.
Sensors (Basel). 2017 Oct 11;17(10):2317. doi: 10.3390/s17102317.
The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a low-cost and non-contact displacement measurement that converts the movement of an object, mostly an attached marker, in the captured images into structural displacement. However, there is limited research on addressing light-induced measurement error caused by the inevitable sunlight in field-testing conditions. This study presents a computer vision-based displacement measurement approach tailored to a field-testing environment with enhanced robustness to strong sunlight. An image-processing algorithm with an adaptive region-of-interest (ROI) is proposed to reliably determine a marker's location even when the marker is indistinct due to unfavorable light. The performance of the proposed system is experimentally validated in both laboratory-scale and field experiments.
土木工程结构的位移响应能够提供有关结构行为的重要信息,有助于评估结构的安全性和适用性。使用传统设备(如线性可变差动变压器(LVDT))进行位移测量具有挑战性,因为传感器安装不便,通常需要额外的临时结构。计算机视觉提供了一种很有前景的替代方法,它通常能提供低成本的非接触式位移测量,即将捕获图像中物体(主要是附着的标记)的移动转换为结构位移。然而,针对现场测试条件下不可避免的阳光导致的光致测量误差,相关研究较少。本研究提出了一种基于计算机视觉的位移测量方法,该方法适用于现场测试环境,对强光具有更强的鲁棒性。提出了一种具有自适应感兴趣区域(ROI)的图像处理算法,即使在光线不利导致标记不清晰的情况下,也能可靠地确定标记的位置。所提系统的性能在实验室规模实验和现场实验中均得到了实验验证。