Vision-Based Faint Vibration Extraction Using Singular Value Decomposition

Vibration measurement is important for understanding the behavior of engineering structures. Unlike conventional contact-type measurements, vision-based methodologies have attracted a great deal of attention because of the advantages of remote measurement, nonintrusive characteristic, and no mass in...

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Main Authors: Xiujun Lei, Jie Guo, Chang’an Zhu
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/306865
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spelling doaj-6231b9a7602a405b94daef55cdb7ce462020-11-25T00:33:44ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/306865306865Vision-Based Faint Vibration Extraction Using Singular Value DecompositionXiujun Lei0Jie Guo1Chang’an Zhu2Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China (USTC), Hefei, Anhui 230027, ChinaDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China (USTC), Hefei, Anhui 230027, ChinaDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China (USTC), Hefei, Anhui 230027, ChinaVibration measurement is important for understanding the behavior of engineering structures. Unlike conventional contact-type measurements, vision-based methodologies have attracted a great deal of attention because of the advantages of remote measurement, nonintrusive characteristic, and no mass introduction. It is a new type of displacement sensor which is convenient and reliable. This study introduces the singular value decomposition (SVD) methods for video image processing and presents a vibration-extracted algorithm. The algorithms can successfully realize noncontact displacement measurements without undesirable influence to the structure behavior. SVD-based algorithm decomposes a matrix combined with the former frames to obtain a set of orthonormal image bases while the projections of all video frames on the basis describe the vibration information. By means of simulation, the parameters selection of SVD-based algorithm is discussed in detail. To validate the algorithm performance in practice, sinusoidal motion tests are performed. Results indicate that the proposed technique can provide fairly accurate displacement measurement. Moreover, a sound barrier experiment showing how the high-speed rail trains affect the sound barrier nearby is carried out. It is for the first time to be realized at home and abroad due to the challenge of measuring environment.http://dx.doi.org/10.1155/2015/306865
collection DOAJ
language English
format Article
sources DOAJ
author Xiujun Lei
Jie Guo
Chang’an Zhu
spellingShingle Xiujun Lei
Jie Guo
Chang’an Zhu
Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
Mathematical Problems in Engineering
author_facet Xiujun Lei
Jie Guo
Chang’an Zhu
author_sort Xiujun Lei
title Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
title_short Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
title_full Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
title_fullStr Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
title_full_unstemmed Vision-Based Faint Vibration Extraction Using Singular Value Decomposition
title_sort vision-based faint vibration extraction using singular value decomposition
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description Vibration measurement is important for understanding the behavior of engineering structures. Unlike conventional contact-type measurements, vision-based methodologies have attracted a great deal of attention because of the advantages of remote measurement, nonintrusive characteristic, and no mass introduction. It is a new type of displacement sensor which is convenient and reliable. This study introduces the singular value decomposition (SVD) methods for video image processing and presents a vibration-extracted algorithm. The algorithms can successfully realize noncontact displacement measurements without undesirable influence to the structure behavior. SVD-based algorithm decomposes a matrix combined with the former frames to obtain a set of orthonormal image bases while the projections of all video frames on the basis describe the vibration information. By means of simulation, the parameters selection of SVD-based algorithm is discussed in detail. To validate the algorithm performance in practice, sinusoidal motion tests are performed. Results indicate that the proposed technique can provide fairly accurate displacement measurement. Moreover, a sound barrier experiment showing how the high-speed rail trains affect the sound barrier nearby is carried out. It is for the first time to be realized at home and abroad due to the challenge of measuring environment.
url http://dx.doi.org/10.1155/2015/306865
work_keys_str_mv AT xiujunlei visionbasedfaintvibrationextractionusingsingularvaluedecomposition
AT jieguo visionbasedfaintvibrationextractionusingsingularvaluedecomposition
AT changanzhu visionbasedfaintvibrationextractionusingsingularvaluedecomposition
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