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利用视频摄像图像数据进行振动信号的频率识别。

Frequency identification of vibration signals using video camera image data.

机构信息

Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 70701, Taiwan.

出版信息

Sensors (Basel). 2012 Oct 16;12(10):13871-98. doi: 10.3390/s121013871.

Abstract

This study showed that an image data acquisition system connecting a high-speed camera or webcam to a notebook or personal computer (PC) can precisely capture most dominant modes of vibration signal, but may involve the non-physical modes induced by the insufficient frame rates. Using a simple model, frequencies of these modes are properly predicted and excluded. Two experimental designs, which involve using an LED light source and a vibration exciter, are proposed to demonstrate the performance. First, the original gray-level resolution of a video camera from, for instance, 0 to 256 levels, was enhanced by summing gray-level data of all pixels in a small region around the point of interest. The image signal was further enhanced by attaching a white paper sheet marked with a black line on the surface of the vibration system in operation to increase the gray-level resolution. Experimental results showed that the Prosilica CV640C CMOS high-speed camera has the critical frequency of inducing the false mode at 60 Hz, whereas that of the webcam is 7.8 Hz. Several factors were proven to have the effect of partially suppressing the non-physical modes, but they cannot eliminate them completely. Two examples, the prominent vibration modes of which are less than the associated critical frequencies, are examined to demonstrate the performances of the proposed systems. In general, the experimental data show that the non-contact type image data acquisition systems are potential tools for collecting the low-frequency vibration signal of a system.

摘要

本研究表明,连接高速相机或网络摄像头与笔记本电脑或个人计算机(PC)的图像数据采集系统可以精确地捕捉到大多数主要的振动信号模式,但可能涉及由帧速率不足引起的非物理模式。使用简单的模型,可以正确预测和排除这些模式的频率。提出了两种实验设计,涉及使用 LED 光源和振动器,以演示性能。首先,通过在感兴趣点周围的小区域中对所有像素的灰度级数据求和,增强了例如视频摄像机的原始灰度级分辨率,从 0 到 256 级。通过将表面带有黑线的白纸片附加到正在运行的振动系统上,进一步增强了图像信号,以提高灰度级分辨率。实验结果表明,Prosilica CV640C CMOS 高速相机在 60 Hz 时会产生虚假模式的临界频率,而网络摄像头的临界频率为 7.8 Hz。已证明有几个因素会部分抑制非物理模式,但不能完全消除它们。检查了两个实例,它们的突出振动模式小于相关的临界频率,以演示所提出系统的性能。总的来说,实验数据表明,非接触式图像数据采集系统是采集系统低频振动信号的潜在工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/dbf139bd868c/sensors-12-13871f1.jpg

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