Vision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets for video processing convenience, leading to high installation effort and focus on only single-point displacement measurement, for example, at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multipoint displacement measurement based on a consumer-grade camera for video acquisition and a custom-developed package for video processing. The system has been validated on a cable-stayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. The analysis results indicate that the system provides valuable information about bridge deformation of the order of a few centimetres induced, in this application, by pedestrian passing. The measured data enable accurate estimation of modal frequencies of either the bridge deck or the bridge cables and could be used to investigate variations of modal frequencies under varying pedestrian loads.

Optics-based tracking of civil structures is not new, due to historical application in surveying, but automated applications capable of tracking at rates that capture dynamic effects are now a hot research topic in structural health monitoring. Recent innovations show promise of true non-contacting monitoring capability avoiding the need for physically attached sensor arrays. The paper reviews recent experience using the Imetrum Dynamic Station (DMS) commercial optics-based tracking system on Humber Bridge and Tamar Bridge, aiming to show both the potential and limitations. In particular the paper focuses on the challenges to field application of such a system resulting from camera instability, nature of the target (artificial or structural feature) and illumination. The paper ends with evaluation of a non-proprietary system using a consumer grade camera for cable vibration monitoring to emphasise the potential for lower cost systems where if performance specifications can be relaxed.

Information on deformation is critical for bridge condition evaluation, but accurate characterization, usually via discrete displacement measurements, remains a challenging task. Vision-based systems are promising tools, possessing advantages of easy installation, low cost, and adequate resolution in time and frequency domains. However, vision-based monitoring faces several field challenges and might fail to achieve the required level of working performance in some real-world test conditions (e.g., involving low-contrast patterns and mounting instability of optical sensors). To make the best use of the potential of vision-based systems, a mixed sensing system consisting of a consumer-grade camera and an accelerometer is proposed in this study for accurate displacement measurement. The system considers automatic compensation of camera shake and involves an autonomous data fusion process for noise reduction. The proposed system is demonstrated by a field monitoring test on a short-span railway bridge and is validated to offer higher accuracy and wider frequency range than using a camera alone. Displacement data by the mixed system are demonstrated to be viable for estimating bridge influence line (IL), indicating the potential for bridge condition assessment.