Non-target Structural Displacement Measurement Using Reference Frame Based Deepflow
Jongbin Won, Jong-Woong Park, and Do-Soo Moon

TL;DR
This paper introduces a reference frame based Deepflow algorithm with masking and filtering for accurate, cost-effective, and flexible non-target structural displacement measurement using computer vision, validated on a cantilevered beam.
Contribution
It presents a novel CV method that overcomes feature detection issues and drift, enabling precise displacement measurement without natural features.
Findings
Validated on a cantilevered beam under various conditions
Achieved high accuracy compared to laser displacement sensors
Flexible in measuring any region without natural features
Abstract
Structural displacement is crucial for structural health monitoring, although it is very challenging to measure in field conditions. Most existing displacement measurement methods are costly, labor intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV) based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame based Deepflow algorithm integrated with masking and signal filtering for non-target based displacement measurements. The proposed method allows the user to select points of interest for…
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Taxonomy
TopicsStructural Health Monitoring Techniques · Optical measurement and interference techniques · Advanced Optical Sensing Technologies
