A Vision-Based Sensor for Noncontact Structural Displacement Measurement

Conventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into...

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Main Authors: Dongming Feng, Maria Q. Feng, Ekin Ozer, Yoshio Fukuda
Format: Article
Language:English
Published: MDPI AG 2015-07-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/15/7/16557
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author Dongming Feng
Maria Q. Feng
Ekin Ozer
Yoshio Fukuda
author_facet Dongming Feng
Maria Q. Feng
Ekin Ozer
Yoshio Fukuda
author_sort Dongming Feng
collection DOAJ
description Conventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into a software package for real-time displacement extraction from video images. By simply adjusting the upsampling factor, better subpixel resolution can be easily achieved to improve the measurement accuracy. The performance of the vision sensor is first evaluated through a laboratory shaking table test of a frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Satisfactory agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. Then field tests are carried out on a railway bridge and a pedestrian bridge, through which the accuracy of the vision sensor in both time and frequency domains is further confirmed in realistic field environments. Significant advantages of the noncontact vision sensor include its low cost, ease of operation, and flexibility to extract structural displacement at any point from a single measurement.
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spelling doaj.art-66f87f5355c1454983f5c13a0d64f4842022-12-22T04:03:49ZengMDPI AGSensors1424-82202015-07-01157165571657510.3390/s150716557s150716557A Vision-Based Sensor for Noncontact Structural Displacement MeasurementDongming Feng0Maria Q. Feng1Ekin Ozer2Yoshio Fukuda3Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USADepartment of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USADepartment of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USADepartment of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USAConventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into a software package for real-time displacement extraction from video images. By simply adjusting the upsampling factor, better subpixel resolution can be easily achieved to improve the measurement accuracy. The performance of the vision sensor is first evaluated through a laboratory shaking table test of a frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Satisfactory agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. Then field tests are carried out on a railway bridge and a pedestrian bridge, through which the accuracy of the vision sensor in both time and frequency domains is further confirmed in realistic field environments. Significant advantages of the noncontact vision sensor include its low cost, ease of operation, and flexibility to extract structural displacement at any point from a single measurement.http://www.mdpi.com/1424-8220/15/7/16557vision sensordisplacementtemplate matchingupsampled cross correlationsubpixel resolutioncivil engineering structures
spellingShingle Dongming Feng
Maria Q. Feng
Ekin Ozer
Yoshio Fukuda
A Vision-Based Sensor for Noncontact Structural Displacement Measurement
Sensors
vision sensor
displacement
template matching
upsampled cross correlation
subpixel resolution
civil engineering structures
title A Vision-Based Sensor for Noncontact Structural Displacement Measurement
title_full A Vision-Based Sensor for Noncontact Structural Displacement Measurement
title_fullStr A Vision-Based Sensor for Noncontact Structural Displacement Measurement
title_full_unstemmed A Vision-Based Sensor for Noncontact Structural Displacement Measurement
title_short A Vision-Based Sensor for Noncontact Structural Displacement Measurement
title_sort vision based sensor for noncontact structural displacement measurement
topic vision sensor
displacement
template matching
upsampled cross correlation
subpixel resolution
civil engineering structures
url http://www.mdpi.com/1424-8220/15/7/16557
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