Zhu Andong, Gong Xinlong, Zhou Jie, Zhang Xiaolong, Zhang Dashan
College of Engineering, Anhui Agricultural University, Hefei 230036, China.
Intelligent Agricultural Machinery Laboratory of Anhui Province, Anhui Agricultural University, Hefei 230036, China.
Sensors (Basel). 2024 Jul 8;24(13):4413. doi: 10.3390/s24134413.
As a non-contact method, vision-based measurement for vibration extraction and modal parameter identification has attracted much attention. In most cases, artificial textures are crucial elements for visual tracking, and this feature limits the application of vision-based vibration measurement on textureless targets. As a computation technique for visualizing subtle variations in videos, the video magnification technique can analyze modal responses and visualize modal shapes, but the efficiency is low, and the processing results contain clipping artifacts. This paper proposes a novel method for the application of a modal test. In contrast to the deviation magnification that exaggerates subtle geometric deviations from only a single image, the proposed method extracts vibration signals with sub-pixel accuracy on edge positions by changing the perspective of deviations from space to timeline. Then, modal shapes are visualized by decoupling all spatial vibrations following the vibration theory of continuous linear systems. Without relying on artificial textures and motion magnification, the proposed method achieves high operating efficiency and avoids clipping artifacts. Finally, the effectiveness and practical value of the proposed method are validated by two laboratory experiments on a cantilever beam and an arch dam model.
作为一种非接触式方法，基于视觉的振动提取和模态参数识别测量受到了广泛关注。在大多数情况下，人工纹理是视觉跟踪的关键要素，而这一特性限制了基于视觉的振动测量在无纹理目标上的应用。作为一种用于可视化视频中细微变化的计算技术，视频放大技术可以分析模态响应并可视化模态形状，但效率较低，且处理结果包含裁剪伪影。本文提出了一种用于模态测试的新方法。与仅从单个图像中夸大细微几何偏差的偏差放大不同，该方法通过将偏差的视角从空间转换到时间线，在边缘位置以亚像素精度提取振动信号。然后，根据连续线性系统的振动理论，通过解耦所有空间振动来可视化模态形状。该方法无需依赖人工纹理和运动放大，实现了高运行效率并避免了裁剪伪影。最后，通过在悬臂梁和拱坝模型上进行的两个实验室实验验证了该方法的有效性和实用价值。
