Long-term displacement measurement system for bridge bearing capable of camera reposition

Abstract

Bridge bearings are critical components that counteract stresses from thermal expansion and traffic loads. Their malfunction due to significant deviations from the intended positions can compromise structural safety. Thus, monitoring their displacement is essential. Previous studies utilized computer vision methods for measuring bearing displacement. However, field-installed cameras often experience movement, resulting in measurement inaccuracies. This paper introduces a computer vision-based method for measuring the six degrees of freedom (6-DOF) displacement of a bridge bearing while correcting for camera ego-motion. A pair of three-dimensional (3D) markers is affixed to both the top and bottom of the bearing. The 3D positions of these markers in relation to the camera are determined using the perspective-n-point method. Employing a formula introduced in this study, we calculate the relative pose between the markers, representing the 6-DOF bearing displacement with camera ego-motion correction. This method’s effectiveness is confirmed through both laboratory-scale and field experiments.