Accurate structural displacement monitoring by data fusion of a consumer-grade camera and accelerometers

The displacement responses of bridge structures are critical both for structural health monitoring and structural safety evaluation. Using vision-based sensors to measure structural displacement responses is an effective method and has attracted considerable attention owing to its advantages of achieving non-contact, time-saving, and full-field measurements. However, there are several obstacles, including the limited frame rate, insufficient accuracy in large-scale measurements, and camera instability, which prevent the application of vision-based sensors. To overcome the shortcomings and improve the accuracies of the vision-based sensors, a displacement monitoring system combined with a consumer-grade camera and accelerometers was developed. Accelerometers attached to the target structures were used to reconstruct the dynamic displacement for data fusion with the vision-based displacement, while an accelerometer attached to the camera was used for camera vibration cancellation. Dynamic loading tests on a self–anchored suspension model bridge were conducted and results of the proposed system, the linear variable differential transformers, and a conventional vision-based system were compared. Field tests on a steel–concrete composite continuous beam bridge and a cable-stayed railway bridge were conducted, and the potential of the proposed system for use in real structures was validated.

» Author: Tong Wu, Liang Tang, Shuai Shao, Xiangyu Zhang, Yijun Liu, Zhixiang Zhou, Xiaolei Qi

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


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