Vibration analysis is crucial for structural health monitoring and fault diagnosis. Conventional contact sensors present limitations, prompting the adoption of non-contact methods such as laser Doppler vibration measurements and computer vision-based techniques. Among these, phase-based video motion magnification has gained prominence for its high resolution and ability to capture comprehensive vibration data across the entire field. However, traditional video motion magnification methods are often affected by noise and artifacts when facing micro vibration measurements. Especially at high magnification, artifacts such as ”double edges” often appear, which seriously affects the accuracy of vibration analysis. In addition, for complex structures, the existing methods still have some difficulties in extracting vibration modes and maintaining fine motion details. Therefore, we propose a novel method for micro-amplitude vibration magnification and a combination of the Horn–Schunck method and the motion intensity averaging method for non-contact vibration displacement measurement. The proposed method uses a complex steerable pyramid to decompose the video into multi-scale and multi-directional sub-bands, extract the phase variations of interest and magnify them, and then an optimized one-dimensional row-gradient domain-guided image filter is used to finely eliminate the double edges, artifacts, and other noises in the high-frequency sub-bands, and finally synthesize the motion-magnified video. Experimental validations on a vibration platform and real structural elements, including a three-story building and an aluminum cantilever beam, demonstrate the method’s superiority in preserving structural clarity and minimizing information loss. Our approach significantly enhances structural vibration analysis, offering accurate frequency identification and mode shape extraction.

中文翻译：

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一种新型的基于相位的视频运动放大非接触微振幅振动测量方法

振动分析对于结构健康监测和故障诊断至关重要。传统的接触式传感器存在局限性，促使人们采用非接触式方法，例如激光多普勒振动测量和基于计算机视觉的技术。其中，基于相位的视频运动放大因其高分辨率和捕获整个领域的综合振动数据的能力而受到关注。然而，传统的视频运动放大方法在面对微振动测量时常常受到噪声和伪影的影响。特别是在高倍放大倍数下，经常出现“双棱”等伪影，严重影响振动分析的准确性。此外，对于复杂结构，现有方法在提取振动模式和保持精细运动细节方面仍然存在一些困难。因此，我们提出了一种新的微振幅振动放大方法，以及结合 Horn-Schunck 方法和运动强度平均方法的非接触振动位移测量。该方法使用复杂的可操纵金字塔将视频分解为多尺度和多方向的子带，提取感兴趣的相位变化并将其放大，然后优化的一维行梯度域引导图像滤波器为用于精细消除高频子带中的双边缘、伪影和其他噪声，最终合成运动放大视频。对振动平台和真实结构元件（包括三层建筑和铝悬臂梁）的实验验证证明了该方法在保持结构清晰度和最大限度地减少信息丢失方面的优越性。我们的方法显着增强了结构振动分析，提供准确的频率识别和振型提取。