Robust vision sensor for multi-point displacement monitoring of bridges in the field

Abstract Computer vision sensors have great potential for accurate remote displacement monitoring in the field. This paper presents InnoVision, a video image processing technique developed by the authors to address a number of difficulties associated with the application of the vision sensors to monitoring structural displacement responses in the outdoor condition that are rarely comprehensively studied in literatures. First, limited lighting condition in the field presents a challenge to tracking low contrast features on the structural surface using intensity-based template matching algorithms. For tackling this challenge, a gradient based template matching algorithm is formulated. Second, to cost-effectively monitor structural displacements at multiple points using one camera, widely used interpolation subpixel methods are investigated and incorporated into InnoVision. Third, camera vibration in the field causes displacement measurement errors. A practical solution is proposed by applying the multi-point monitoring to track both the structure and a stationary reference point. The effect of the camera vibration can be canceled by subtracting the reference displacement from the structural displacements. Several laboratory and field tests are conducted to evaluate the InnoVision’s performance. One of the field tests is conducted in a challenging low lighting condition at night on a steel girder bridge to validate the robustness of InnoVision in comparison with two other vision sensing methods. Another field test is carried out on the Manhattan Bridge to demonstrate the efficacy of the proposed technique for canceling camera vibration and the capability of InnoVision to simultaneously monitor multiple points under the effect of camera vibration.