Structural Dynamics Identification Using Motion Estimation and Video Magnification

使用运动估计和视频放大进行结构动力学识别

基本信息

  • 批准号:
    1762809
  • 负责人:
  • 金额:
    $ 37.64万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-09-15 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

This project aims to explore the use of a non-contact, video camera-based method to identify small motions and dynamic behavior of structures. This has the potential to help engineers understand complex dynamic behavior of 3D structures, including, for example, wind turbines, bridges, aircraft, ships, and automobiles. This will help in structural health monitoring, as well as in testing numerical model predictions of deformations of large, complex structures. Videos can be recorded, and deformations and dynamic behavior distilled using a portable electronic device application (app) developed for a cell phone. This will permit simplified use of the technology by researchers, design engineers and field inspectors. The research team will work with high school students to integrate the video sensing technology into their curriculum. The project will also involve female and minority students.The primary research objective of this project is to understand and quantify the relationship between the structural dynamics extracted via camera video motion magnification and the true dynamic motion. The project has the potential to transform the way large-scale experimental modal analysis and three-dimensional (3D) structural dynamics identification is currently performed. The successful completion of the work will lead to a better understanding of vision-based structural dynamic parameter extraction and how the processed data is affected by environmental and operational variabilities. This work will integrate the phase-based motion estimation technique with 3D digital image correlation and point tracking to achieve an understanding of how two-dimensional camera measurements can be used to extract quantitative 3D motion. The successful outcomes of this project will address the existing knowledge gap between the factors that contaminate the related algorithms and the processed results, while quantifying uncertainty for video-based structural dynamics identification. The research will generate a systematic understanding of how extracted optical flows are associated with dynamic motions. Achieving a quantitative understanding of how different parameters influence the results for phase-based motion extraction and video magnification will lead to a transformative new approach for non-contact measurement that can impact system identification, validation, and structural health monitoring of various infrastructure systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
本项目旨在探索使用一种非接触的、基于摄像机的方法来识别结构的小运动和动态行为。 这有可能帮助工程师了解3D结构的复杂动态行为,包括风力涡轮机、桥梁、飞机、船舶和汽车。 这将有助于结构健康监测,以及测试大型复杂结构变形的数值模型预测。 可以使用为手机开发的便携式电子设备应用程序(app)记录视频,并提取变形和动态行为。 这将使研究人员、设计工程师和现场视察员能够简化技术的使用。 研究小组将与高中生合作,将视频传感技术融入他们的课程。该项目的主要研究目标是了解和量化通过摄像机视频运动放大提取的结构动力学与真实动态运动之间的关系。该项目有可能改变目前进行的大规模实验模态分析和三维(3D)结构动力学识别的方式。这项工作的成功完成将有助于更好地理解基于视觉的结构动态参数提取以及处理后的数据如何受到环境和操作变量的影响。 这项工作将基于相位的运动估计技术与3D数字图像相关和点跟踪相结合,以了解如何使用二维相机测量来提取定量3D运动。该项目的成功成果将解决污染相关算法的因素与处理结果之间的现有知识差距,同时量化基于视频的结构动力学识别的不确定性。 这项研究将产生一个系统的理解,如何提取光流与动态运动。实现对不同参数如何影响基于相位的运动提取和视频放大结果的定量理解,将为非接触式测量带来变革性的新方法,可以影响系统识别,验证,该奖项反映了NSF的法定使命,并通过使用基金会的智力价值进行评估,被认为值得支持和更广泛的影响审查标准。

项目成果

期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Quantification of phase-based magnified motion using image enhancement and optical flow techniques
使用图像增强和光流技术量化基于相位的放大运动
  • DOI:
    10.1016/j.measurement.2021.110508
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    5.6
  • 作者:
    Valente, Nicholas A.;do Cabo, Celso T.;Mao, Zhu;Niezrecki, Christopher
  • 通讯作者:
    Niezrecki, Christopher
Volumetric Motion Magnification: Subtle Motion Extraction from 4D Data
体积运动放大:从 4D 数据中提取细微运动
  • DOI:
    10.1016/j.measurement.2021.109211
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    5.6
  • 作者:
    Southwick, Matthew;Mao, Zhu;Niezrecki, Christopher
  • 通讯作者:
    Niezrecki, Christopher
An investigation on the relationship between distortions in the motion magnified videos, and the choice of filter bank
运动放大视频失真与滤波器组选择关系的研究
  • DOI:
    10.1117/12.2515538
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sarrafi, Aral;Mao, Zhu
  • 通讯作者:
    Mao, Zhu
Streamlined particle filtering of phase-based magnified videos for quantified operational deflection shapes
  • DOI:
    10.1016/j.ymssp.2022.109233
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    8.4
  • 作者:
    Nicholas A. Valente;Aral Sarrafi;Zhu Mao;C. Niezrecki
  • 通讯作者:
    Nicholas A. Valente;Aral Sarrafi;Zhu Mao;C. Niezrecki
A Complex Convolution Kernel-Based Optical Displacement Sensor
  • DOI:
    10.1109/jsen.2020.2986240
  • 发表时间:
    2020-09
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Matthew Southwick;Zhu Mao;C. Niezrecki
  • 通讯作者:
    Matthew Southwick;Zhu Mao;C. Niezrecki
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Zhu Mao其他文献

Mode extraction on wind turbine blades via phase-based video motion estimation
通过基于相位的视频运动估计对风力涡轮机叶片进行模式提取
Uncertainty quantification of phase-based motion estimation on noisy sequence of images
图像噪声序列上基于相位的运动估计的不确定性量化
Synergistic dual‑boron framework and embedded spirofluorene enable efficient MR-TADF emitters with anti-quenching effect and low efficiency roll-off
协同双硼骨架和嵌入螺芴实现了具有抗猝灭效应和低效率滚降的高效 MR-TADF 发射体
  • DOI:
    10.1016/j.cej.2025.165337
  • 发表时间:
    2025-09-01
  • 期刊:
  • 影响因子:
    13.200
  • 作者:
    Zhiwei Ma;Yuyuan Wang;Jinkun Bian;Xiang Long;Gaoyu Li;Zhu Mao;Zhiyong Yang;Juan Zhao;Zhenguo Chi
  • 通讯作者:
    Zhenguo Chi
Achieving tunable dual-emissive and high-contrast mechanochromic materials by manipulating steric hindrance effects
通过操纵空间位阻效应实现可调谐双发射和高对比度力致变色材料
  • DOI:
    10.1039/c8tc06039h
  • 发表时间:
    2019-03
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    Zongliang Xie;Tongtong Su;Eethamukkala Ubba;Huangjun Deng;Zhu Mao;Tao Yu;Ting Zheng;Yi Zhang;Siwei Liu;Zhenguo Chi
  • 通讯作者:
    Zhenguo Chi

Zhu Mao的其他文献

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{{ truncateString('Zhu Mao', 18)}}的其他基金

Structural Dynamics Identification Using Motion Estimation and Video Magnification
使用运动估计和视频放大进行结构动力学识别
  • 批准号:
    2230218
  • 财政年份:
    2022
  • 资助金额:
    $ 37.64万
  • 项目类别:
    Standard Grant

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  • 批准年份:
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