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A Compressed Sensing Approach to Operational Modal Analysis Using Phase-Based Video Motion Magnification

机译:基于相位的视频运动放大倍数的压缩传感方法用于操作模态分析

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Phase-based video modal analysis is a modern method of extracting a modal model from a video of a structure's vibration response. The high spatial resolution inherent to cameras results in high-resolution mode shapes, an obvious advantage in any damage detection application. Unfortunately, the method is limited by the sampling rate of the camera, meaning the high-frequency modes often vital for damage localisation are unobtainable. This paper presents a novel application of compressive sensing to the phase-based video modal analysis method. Compressive sensing allows for signals to be recovered from far fewer samples than traditionally required by the Shannon-Nyquist theorem, thus extending the measurement range of a standard camera.
机译:基于相位的视频模态分析是一种从结构振动响应视频中提取模态模型​​的现代方法。摄像机固有的高空间分辨率可产生高分辨率的模式形状,这在任何损坏检测应用中都具有明显的优势。不幸的是,该方法受到相机采样率的限制,这意味着无法获得通常对损伤定位至关重要的高频模式。本文提出了压缩感知技术在基于相位的视频模态分析方法中的新应用。压缩感测允许从比Shannon-Nyquist定理传统上所需的样本少得多的样本中恢复信号,从而扩展了标准相机的测量范围。

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