Accurate structural displacement monitoring by data fusion of a consumer-grade camera and accelerometers. (1st July 2022)

• Record Type: Journal Article
• Authors: Wu, Tong; Tang, Liang; Shao, Shuai; Zhang, Xiangyu; Liu, Yijun; Zhou, Zhixiang; Qi, Xiaolei
• Is Part Of: Engineering structures. Volume 262(2022)
• Publication Date: 2022-07-01
• Subjects: Bridge displacement monitoring -- Vision-based system -- Displacement reconstruction -- Data fusion -- Camera vibration cancellation; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2022.114303
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: A displacement monitoring system combined with a consumer-grade camera and accelerometers is developed. An improved template matching algorithm based on downsampling correlation calculation is proposed. The vibration of the camera is reconstructed and canceled by the acceleration from the accelerometer attached to the camera. The efficiency is validated by a laboratory test and a field test. Abstract: 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.