Real‐time displacement measurement for long‐span bridges using a compact vision‐based system with speed‐optimized template matching

Abstract

This paper introduces a new accelerating algorithm, efficient match slimmer (EMS), specifically designed to lighten computational loads of sophisticated template matching algorithms, enabling these algorithms to be effectively run on single-board computers. Utilizing EMS in conjunction with a robust template matching algorithm, we have developed Raspberry Vision—a compact, cost-effective, and real-time vision-based system. Its compactness and portability facilitate a practical measurement strategy that not only minimizes the camera-to-target distance but also simplifies the camera calibration process in bridge displacement monitoring, thereby enhancing measurement accuracy. The performance of the system is estimated on two operational suspension bridges. The results demonstrate that Raspberry Vision, equipped with the measurement strategy, can significantly improve the measurement accuracy in the long-span bridge test and is also suitable for cross-sea bridge measurements.