Computer vision for SHM of civil infrastructure: From dynamic response measurement to damage detection – A review

Abstract

To address the limitations of current sensor systems for field applications, the research community has been actively exploring new technologies that can advance the state-of-the-practice in structural health monitoring (SHM). Thanks to the rapid advances in computer vision, the camera-based noncontact vision sensor has emerged as a promising alternative to conventional contact sensors for structural dynamic response measurement and health monitoring. Significant advantages of the vision sensor include its low cost, ease of setup and operation, and flexibility to extract displacements of any points on the structure from a single video measurement. This review paper is intended to summarize the collective experience that the research community has gained from the recent development and validation of the vision-based sensors for structural dynamic response measurement and SHM. General principles of the vision sensor systems are firstly presented by reviewing different template matching techniques for tracking targets, coordinate conversion methods for determining calibration factors to convert image pixel displacements to physical displacements, measurements by tracking artificial targets vs. natural targets, measurements in real time vs. by post-processing, etc. Then the paper reviews laboratory and filed experimentations carried out to evaluate the performance of the vision sensors, followed by a discussion on measurement error sources and mitigation methods. Finally, applications of the measured displacement data for SHM are reviewed, including examples of structural modal property identification, structural model updating, damage detection, and cable force estimation.