Suppr超能文献

利用图像凸壳优化开发无标记夜视位移传感器系统。

Development of Marker-Free Night-Vision Displacement Sensor System by Using Image Convex Hull Optimization.

机构信息

Department of Architectural Engineering, Yonsei University, 50 Yonseiro, Seodaemun-gu, Seoul 120-749, Korea.

出版信息

Sensors (Basel). 2018 Nov 27;18(12):4151. doi: 10.3390/s18124151.

Abstract

Vision-based displacement sensors (VDSs) have the potential to be widely used in the structural health monitoring field, because the VDSs are generally easier to install and have higher applicability to the existing structures compared to the other conventional displacement sensors. However, the VDS also has disadvantages, in that ancillary markers are needed for extracting displacement data and data reliability is significantly lowered at night. In this study, a night vision displacement sensor (NVDS) was proposed to overcome the aforementioned two limitations. First, a non-contact NVDS system is developed with the installation of the infrared (IR) pass filter. Since it utilizes the wavelength of the infrared region and it is not sensitive to the change of a visible ray, it can precisely extract the shape information of the structure even at night. Second, a technique to extract the feature points from the images without any ancillary marker was formulated through an image convex hull optimization. Finally, the experimental tests of a three-story scaled model were performed to investigate the effectiveness of proposed NVDS at night. The results demonstrate that the NVDS has sufficiently high accuracy even at night and it can precisely measure the dynamic characteristics such as mode shapes and natural frequencies of the structure. The proposed system and formulation would extend the applicability of vision sensor not only into night-time measure but also marker-free measure.

摘要

基于视觉的位移传感器(VDS)在结构健康监测领域具有广泛的应用潜力,因为与其他传统位移传感器相比,VDS 通常更容易安装,对现有结构具有更高的适用性。然而,VDS 也有缺点,因为需要辅助标记来提取位移数据,并且数据可靠性在夜间显著降低。在本研究中,提出了一种夜视位移传感器(NVDS)来克服上述两个限制。首先,开发了一种非接触式 NVDS 系统,安装了红外(IR)通滤波器。由于它利用了红外区域的波长,并且对可见光的变化不敏感,因此即使在夜间也可以精确提取结构的形状信息。其次,通过图像凸壳优化制定了一种无需任何辅助标记即可从图像中提取特征点的技术。最后,对一个三层比例模型进行了实验测试,以研究 NVDS 在夜间的有效性。结果表明,即使在夜间,NVDS 也具有足够高的精度,并且可以精确测量结构的动态特性,如模态形状和固有频率。所提出的系统和公式将不仅扩展视觉传感器在夜间测量的适用性,还扩展无标记测量的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/964c/6308800/dbe07ecad511/sensors-18-04151-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验