• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

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.

DOI:10.3390/s121013871
PMID:23202026
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3545597/
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/3545597/8d18c27b4fe9/sensors-12-13871f20.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/dbf139bd868c/sensors-12-13871f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/0a0fd93a06b7/sensors-12-13871f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/35c7b773da60/sensors-12-13871f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/7b6613bbf380/sensors-12-13871f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/99bd6e4cc817/sensors-12-13871f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/ed6d0421cd01/sensors-12-13871f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/aa309594e6c0/sensors-12-13871f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/121e642016bb/sensors-12-13871f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/3558b7d619e2/sensors-12-13871f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/61adae16f995/sensors-12-13871f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/5e54e2939ff6/sensors-12-13871f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/5e8cba474733/sensors-12-13871f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/f2766d36cdcf/sensors-12-13871f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/a2397f94b800/sensors-12-13871f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/d28dd366a64d/sensors-12-13871f15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/dd87da5a5d78/sensors-12-13871f16a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/37fe057b4013/sensors-12-13871f17.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/03f45d1a07a6/sensors-12-13871f18a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/ae268bef1b4b/sensors-12-13871f19.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/8d18c27b4fe9/sensors-12-13871f20.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/dbf139bd868c/sensors-12-13871f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/0a0fd93a06b7/sensors-12-13871f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/35c7b773da60/sensors-12-13871f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/7b6613bbf380/sensors-12-13871f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/99bd6e4cc817/sensors-12-13871f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/ed6d0421cd01/sensors-12-13871f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/aa309594e6c0/sensors-12-13871f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/121e642016bb/sensors-12-13871f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/3558b7d619e2/sensors-12-13871f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/61adae16f995/sensors-12-13871f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/5e54e2939ff6/sensors-12-13871f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/5e8cba474733/sensors-12-13871f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/f2766d36cdcf/sensors-12-13871f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/a2397f94b800/sensors-12-13871f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/d28dd366a64d/sensors-12-13871f15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/dd87da5a5d78/sensors-12-13871f16a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/37fe057b4013/sensors-12-13871f17.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/03f45d1a07a6/sensors-12-13871f18a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/ae268bef1b4b/sensors-12-13871f19.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b77d/3545597/8d18c27b4fe9/sensors-12-13871f20.jpg

相似文献

1
Frequency identification of vibration signals using video camera image data.利用视频摄像图像数据进行振动信号的频率识别。
Sensors (Basel). 2012 Oct 16;12(10):13871-98. doi: 10.3390/s121013871.
2
Flexible Fiber-Optic High-Speed Imaging of Vocal Fold Vibration: A Preliminary Report.声带振动的柔性光纤高速成像:初步报告
J Voice. 2017 Mar;31(2):175-181. doi: 10.1016/j.jvoice.2016.07.015.
3
Recording human electrocorticographic (ECoG) signals for neuroscientific research and real-time functional cortical mapping.记录用于神经科学研究和实时功能性皮层图谱绘制的人类皮层脑电图(ECoG)信号。
J Vis Exp. 2012 Jun 26(64):3993. doi: 10.3791/3993.
4
Vibration Detection and Degraded Image Restoration of Space Camera Based on Correlation Imaging of Rolling-Shutter CMOS.基于卷帘 CMOS 相关成像的空间相机振动检测与降质图像恢复
Sensors (Basel). 2023 Jun 27;23(13):5953. doi: 10.3390/s23135953.
5
Investigation of Flexible High-Speed Video Nasolaryngoscopy.柔性高速视频鼻咽喉镜检查的研究
J Voice. 2018 Sep;32(5):529-537. doi: 10.1016/j.jvoice.2017.08.017. Epub 2017 Sep 25.
6
[Endoscopic imaging of vocal cord vibrations. Digital high speed recording with various systems].[声带振动的内镜成像。使用各种系统的数字高速记录]
HNO. 1996 Dec;44(12):685-93. doi: 10.1007/s001060050076.
7
Multimode vibration analysis with high-speed TV holography and a spatiotemporal 3D Fourier transform method.基于高速电视全息术和时空三维傅里叶变换方法的多模态振动分析
Opt Express. 2009 Sep 28;17(20):18014-25. doi: 10.1364/OE.17.018014.
8
Influence of acquisition frame-rate and video compression techniques on pulse-rate variability estimation from vPPG signal.采集帧率和视频压缩技术对基于视频光电容积脉搏波描记(vPPG)信号的脉率变异性估计的影响。
Biomed Tech (Berl). 2019 Feb 25;64(1):53-65. doi: 10.1515/bmt-2016-0234.
9
Vibration frequency measurement using a local multithreshold technique.使用局部多阈值技术进行振动频率测量。
Opt Express. 2013 Nov 4;21(22):26198-208. doi: 10.1364/OE.21.026198.
10
Our solution for fusion of simultaneusly acquired whole body scintigrams and optical images, as usesful tool in clinical practice in patients with differentiated thyroid carcinomas after radioiodine therapy. A useful tool in clinical practice.我们用于同时采集的全身闪烁扫描图与光学图像融合的解决方案,是放射性碘治疗后分化型甲状腺癌患者临床实践中的有用工具。临床实践中的有用工具。
Hell J Nucl Med. 2017 Sep-Dec;20 Suppl:159.

引用本文的文献

1
Non-Invasive Inspections: A Review on Methods and Tools.非侵入式检测:方法与工具综述。
Sensors (Basel). 2021 Dec 19;21(24):8474. doi: 10.3390/s21248474.

本文引用的文献

1
A Novel Pulse Measurement System by Using Laser Triangulation and a CMOS Image Sensor.一种基于激光三角测量法和CMOS图像传感器的新型脉搏测量系统。
Sensors (Basel). 2007 Dec 19;7(12):3366-3385. doi: 10.3390/s7123366.
2
CMOS Image Sensors for High Speed Applications.高速应用的 CMOS 图像传感器。
Sensors (Basel). 2009;9(1):430-44. doi: 10.3390/s90100430. Epub 2009 Jan 13.
3
Response identification in the extremely low frequency region of an electret condenser microphone.驻极体电容传声器极低频响应的识别
Sensors (Basel). 2011;11(1):623-37. doi: 10.3390/s110100623. Epub 2011 Jan 10.
4
A Parkinson's disease measurement system using laser lines and a CMOS image sensor.使用激光线和 CMOS 图像传感器的帕金森病测量系统。
Sensors (Basel). 2011;11(2):1461-75. doi: 10.3390/s110201461. Epub 2011 Jan 26.