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A Vision-Based Sensor for Noncontact Structural Displacement Measurement.

Feng D, Feng MQ, Ozer E, Fukuda Y - Sensors (Basel) (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA. df2465@columbia.edu.

ABSTRACT
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.

No MeSH data available.


Laboratory test: (a) Shaking table test setup; (b) Vision sensor system setup.
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sensors-15-16557-f005: Laboratory test: (a) Shaking table test setup; (b) Vision sensor system setup.

Mentions: The performance of the proposed vision sensor is first evaluated through a shaking table test of a scaled three-story frame structure in the Carleton Laboratory at Columbia University, as shown in Figure 5. The aluminum frame structure is bolt-connected for all the column-floor connections.


A Vision-Based Sensor for Noncontact Structural Displacement Measurement.

Feng D, Feng MQ, Ozer E, Fukuda Y - Sensors (Basel) (2015)

Laboratory test: (a) Shaking table test setup; (b) Vision sensor system setup.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541893&req=5

sensors-15-16557-f005: Laboratory test: (a) Shaking table test setup; (b) Vision sensor system setup.
Mentions: The performance of the proposed vision sensor is first evaluated through a shaking table test of a scaled three-story frame structure in the Carleton Laboratory at Columbia University, as shown in Figure 5. The aluminum frame structure is bolt-connected for all the column-floor connections.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA. df2465@columbia.edu.

ABSTRACT
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.

No MeSH data available.