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Structural displacement is crucial for structural health monitoring, althoughit is very challenging to measure in field conditions. Most existingdisplacement measurement methods are costly, labor intensive, andinsufficiently accurate for measuring small dynamic displacements. Computervision (CV) based methods incorporate optical devices with advanced imageprocessing algorithms to accurately, cost-effectively, and remotely measurestructural displacement with easy installation. However, non-target based CVmethods are still limited by insufficient feature points, incorrect featurepoint detection, occlusion, and drift induced by tracking error accumulation.This paper presents a reference frame based Deepflow algorithm integrated withmasking and signal filtering for non-target based displacement measurements.The proposed method allows the user to select points of interest for imageswith a low gradient for displacement tracking and directly calculatedisplacement without drift accumulated by measurement error. The proposedmethod is experimentally validated on a cantilevered beam under ambient andoccluded test conditions. The accuracy of the proposed method is compared withthat of a reference laser displacement sensor for validation. The significantadvantage of the proposed method is its flexibility in extracting structuraldisplacement in any region on structures that do not have distinct naturalfeatures.

Non-target Structural Displacement Measurement Using Reference Frame Based Deepflow