Abstract
Structural health monitoring (SHM) techniques are used to assess the behavior of structures during or after construction. The high cost of sensors is the main reason for the limited use of the SHM techniques. The present study investigates the dynamic behavior (dynamic acceleration, semi-static displacement, frequency and damping ratio) of highway steel plate girder bridges using strain measurements. The double filtration and polynomial prediction methods are used to estimate the dynamic behavior of the bridge using real-time strain measurements. To verify the accuracy of the developed method, the field monitoring measurements of the WonHyo bridge is used. The bridge behavior under different truck speeds and weights is observed and evaluated. The displacement and acceleration measurements are used to examine the results of the proposed method. The results of this study demonstrate that the strain measurements can be used to obtain an accurate semi-static displacement and dominant frequency content of the bridge. The accuracy of the developed model for the semi-static and dynamic behaviors is 99% and 69%, respectively.
Highlights
Structural health monitoring (SHM) has become a necessary tool to evaluate the condition of important structures, such as bridges, buildings, tunnels, and so forth
Long-term systems are used for a continuous monitoring of the structures that need real-time performance analysis, on the other hand, short-term monitoring systems are mostly low-cost monitoring systems used to evaluate the performance of existing structures for a short period of time
The present study introduces a low-cost monitoring system to extract the full behavior of a monitoring point, including the accurate dynamic performance, of highway steel bridges using only strain measurements
Summary
Structural health monitoring (SHM) has become a necessary tool to evaluate the condition of important structures, such as bridges, buildings, tunnels, and so forth. Long-term systems are used for a continuous monitoring of the structures that need real-time performance analysis, on the other hand, short-term monitoring systems are mostly low-cost monitoring systems used to evaluate the performance of existing structures for a short period of time. Many researchers developed low-cost monitoring techniques in order to decrease the costs of the long- and short-term assessment of structures. Gulgec et al [2] employed a deep learning algorithm to decrease the cost of SHM by estimating the strain responses from acceleration responses. Jo et al [5] presented a low-cost monitoring technique using global positioning system (GPS) sensors by using four low-cost sensors for estimating the dynamic behavior of structures; the results of this study showed low accuracy, 20–30 cm.
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