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Sensing dynamic displacements in masonry rail bridges using 2D digital image correlation
Author(s) -
Acikgoz Sinan,
DeJong Matthew J.,
Soga Kenichi
Publication year - 2018
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2187
Subject(s) - digital image correlation , distortion (music) , displacement (psychology) , computer vision , repeatability , pixel , artificial intelligence , computer science , engineering , optics , mathematics , electronic engineering , psychology , amplifier , statistics , physics , cmos , psychotherapist
Summary Dynamic displacement measurements provide useful information for the assessment of masonry rail bridges, which constitute a significant part of the bridge stock in the United Kingdom and Europe. Commercial 2D digital image correlation (DIC) techniques are well suited for this purpose. These systems provide precise noncontact displacement measurements simultaneously at many locations of the bridge with an easily configured camera set‐up. However, various sources of errors can affect the resolution, repeatability, and accuracy of DIC field measurements. Typically, these errors are application specific and are not automatically corrected by commercial software. To address this limitation, this paper presents a survey of relevant DIC errors and discusses methods to minimise the influence of these errors during equipment set‐up and data processing. A case study application of DIC for multipoint displacement measurement of a masonry viaduct in Leeds is then described, where potential errors due to lighting changes, image texture, and camera movements are minimised with an appropriate set‐up. Pixel‐metric scaling errors are kept to a minimum with the use of a calibration method, which utilises vanishing points in the image. However, comparisons of DIC relative displacement measurements to complementary strain measurements from the bridge demonstrate that other errors may have significant influence on the DIC measurement accuracy. Therefore, the influence of measurement errors due to lens radial distortion and out‐of‐plane movements is quantified theoretically with pinhole camera and division distortion models. A method to correct for errors due to potential out‐of‐plane movements is then proposed.