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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.


Field test of a railway bridge: (a) Displacement measurement under moving trainloads; (b) Artificial target and natural target.
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sensors-15-16557-f011: Field test of a railway bridge: (a) Displacement measurement under moving trainloads; (b) Artificial target and natural target.

Mentions: In collaboration with the Transportation Technology Center, Inc. (TTCI), field measurements are carried out on a state-of-the-art hybrid composite bridge, which is one of the test-bed bridges in TTCI, Colorado. As shown in Figure 11a, the bridge is 12.8 m long. The train used for the testing has one locomotive and 15 freight cars. Figure 11b shows the artificial target and natural target on the bridge. The video camera is fixed on a tripod and set up at a remote location away from the bridge. This field tests focused on the measurement of the vertical displacement at the mid-span point by the vision sensor. As a reference sensor, a conventional contact-type displacement sensor, i.e., a LVDT, is installed on the mid span of the bridge with one end connected to a stationary reference point on the ground through a string.


A Vision-Based Sensor for Noncontact Structural Displacement Measurement.

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

Field test of a railway bridge: (a) Displacement measurement under moving trainloads; (b) Artificial target and natural target.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16557-f011: Field test of a railway bridge: (a) Displacement measurement under moving trainloads; (b) Artificial target and natural target.
Mentions: In collaboration with the Transportation Technology Center, Inc. (TTCI), field measurements are carried out on a state-of-the-art hybrid composite bridge, which is one of the test-bed bridges in TTCI, Colorado. As shown in Figure 11a, the bridge is 12.8 m long. The train used for the testing has one locomotive and 15 freight cars. Figure 11b shows the artificial target and natural target on the bridge. The video camera is fixed on a tripod and set up at a remote location away from the bridge. This field tests focused on the measurement of the vertical displacement at the mid-span point by the vision sensor. As a reference sensor, a conventional contact-type displacement sensor, i.e., a LVDT, is installed on the mid span of the bridge with one end connected to a stationary reference point on the ground through a string.

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.