Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification
Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification
复制标题
DOI：
10.1016/j.ymssp.2016.08.041
复制
发表时间：
2017-02-15
影响因子：
8.4
通讯作者：
Mascarenas, David
中科院分区：
文献类型：
--
作者：
Yang, Yongchao;Dorn, Charles;Mascarenas, David
实验或操作模态分析传统上需要物理连接的有线或无线传感器来测量结构的振动。这种仪器可能导致轻质结构上的质量负载，并且在大型土木结构上安装和维护是昂贵和耗时的，特别是对于长期应用（例如，结构健康监测），其需要对电缆（有线传感器）进行大量维护或定期更换能源（无线传感器）。此外，这些传感器通常被放置在有限数量的离散位置，提供低的空间感测分辨率，这是很难足够的基于模态的损伤定位，或模型相关性和更新较大规模的结构。扫描激光测振仪等非接触式测量方法可提供高分辨率的传感能力，而不会产生质量负载效应;然而，它们进行的连续测量需要相当长的采集时间。作为一种替代的非接触式方法，数字摄像机成本相对较低，灵活，并提供高空间分辨率，同时，测量。结合基于视觉的算法（例如，图像相关、光流）、基于摄像机的测量已经成功地用于振动测量和随后的模态分析，基于诸如数字图像相关（DIC）和点跟踪的技术。然而，它们通常需要将散斑图案或高对比度标记放置在结构的表面上，这在测量区域较大或不可接近时带来了挑战。这项工作探讨了先进的计算机视觉和视频处理算法，开发了一种新的视频测量和基于视觉的操作（仅输出）模态分析方法，减轻了与现有基于视觉的方法相关的结构表面准备的需要，并且可以以相对有效和自主的方式实现，几乎没有用户监督和校准。首先对振动结构的视频帧应用多尺度图像处理方法，提取编码局部结构振动的局部像素相位，建立全场时空运动矩阵。然后，使用高空间维、低模态维、过完备模型来表示使用模态叠加提取的全场运动矩阵，模态叠加分别由一系列无监督学习模型和技术物理连接和操纵。因此，所提出的方法是能够盲目地提取模态频率，阻尼比，和全场（尽可能多的点的视频帧的像素数）模式形状从视线视频测量的结构。实验室实验室规模的建筑结构和悬臂梁的方法进行了验证。它的输出（视频测量）的能力，只有识别和可视化的弱激发模式进行了演示，并讨论了其实施的几个问题。出版社：Elsevier Ltd
Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. This instrumentation can result in mass-loading on lightweight structures, and is costly and time-consuming to install and maintain on large civil structures, especially for long-term applications (e.g., structural health monitoring) that require significant maintenance for cabling (wired sensors) or periodic replacement of the energy supply (wireless sensors). Moreover, these sensors are typically placed at a limited number of discrete locations, providing low spatial sensing resolution that is hardly sufficient for modal-based damage localization, or model correlation and updating for larger-scale structures. Non-contact measurement methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass-loading effect; however, they make sequential measurements that require considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision-based operational (output-only) modal analysis method that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little user supervision and calibration. First a multi-scale image processing method is applied on the frames of the video of a vibrating structure to extract the local pixel phases that encode local structural vibration, establishing a full-field spatioteMporal motion matrix. Then a high-spatial dimensional, yet low-modal-dimensional, over-complete model is used to represent the extracted full-field motion matrix using modal superposition, which is physically connected and manipulated by a family of unsupervised learning models and techniques, respectively. Thus, the proposed method is able to blindly extract modal frequencies, damping ratios, and full-field (as many points as the pixel number of the video frame) mode shapes from line of sight video measurements of the structure. The method is validated by laboratory experiments on a bench-scale building structure and a cantilever beam. Its ability for output (video measurements)-only identification and visualization of the weakly-excited mode is demonstrated and several issues with its implementation are discussed. Published by Elsevier Ltd.