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Measurements of Strain

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Strain quantifies the deformation of a material under force, typically measured as normal strain, which represents the change in length when compared with the original length. Electrical strain gauges are used for enhanced accuracy. These devices consist of a conductive wire mounted on a paper backing that adheres to the material's surface. These gauges operate on the piezoresistive effect, where the wire's electrical resistance changes in response to mechanical deformation. The strain...

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A Vision-Based Sensor for Noncontact Structural Displacement Measurement.

Dongming Feng¹, Maria Q Feng², Ekin Ozer³

¹Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA. df2465@columbia.edu.

Sensors (Basel, Switzerland)

|July 18, 2015

Summary

This study introduces a novel vision sensor system for remote structural displacement measurement. The system utilizes an advanced template matching algorithm for accurate, real-time tracking of structural movements.

Keywords:

civil engineering structures displacement subpixel resolution template matching upsampled cross correlation vision sensor

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Area of Science:

Structural Engineering
Computer Vision
Measurement Science

Background:

Conventional displacement sensors face practical limitations in structural monitoring.
Remote and non-contact measurement methods are needed for enhanced structural health assessment.

Purpose of the Study:

To develop and validate a vision sensor system for real-time, remote measurement of structural displacements.
To assess the accuracy and feasibility of the vision sensor in laboratory and field conditions.

Main Methods:

Development of a vision sensor system employing an advanced template matching algorithm (upsampled cross-correlation).
Real-time displacement extraction from video images with adjustable subpixel resolution.
Laboratory validation using a shaking table test on a frame structure.
Field tests on a railway bridge and a pedestrian bridge.

Main Results:

The vision sensor system demonstrated satisfactory agreement with high-performance laser displacement sensors in laboratory tests.
Field tests confirmed the accuracy of the vision sensor in both time and frequency domains under realistic conditions.
The system successfully tracked displacements using both artificial and natural targets on structural surfaces.

Conclusions:

The developed non-contact vision sensor system offers a cost-effective, user-friendly, and flexible solution for structural displacement monitoring.
This technology provides accurate remote measurement capabilities, enhancing structural health assessment and safety.
The system's ability to extract displacement data from any point using a single camera represents a significant advancement.