Summary The objectives of this research are (a) to establish a structural health monitoring system for bridge safety evaluation that is suitable for cold, remote regions and (b) to identify the bridge responses under variations in temperature. To achieve this, fiber optic sensors with temperature compensation were selected that were suitable for cold regions. This technique allows monitoring equipment to operate far from the sensor installation site, which avoids exposing much of the equipment to extremely cold temperatures and makes a power supply more accessible. The bridge temperature behavior is studied based on the real‐time field measurement data, and the relationship between the thermal loading and the bridge response is presented.

In bridge health monitoring, tiltmeters have been used for measuring rotation and curvature; however, their application in dynamic parameter identification has been lacking. This study installed fiber Bragg grating (FBG) tiltmeters on the bearings of a bridge and monitored the dynamic rotational angle. The dynamic features, including natural frequencies and mode shapes, have been identified successfully. The innovation presented in this paper is the first-time use of FBG tiltmeter readings to identify the natural frequencies of a long-span steel girder bridge. The identified results have been verified using a bridge finite element model. This paper introduces a new method for the dynamic monitoring of a bridge using FBG tiltmeters. Limitations and future research directions are also discussed in the conclusion.

This paper aims to explore fundamental characteristics of bridge vibration spectra to potentially evaluate soil-abutment interactions and changes in abutment earth pressures. To this aim, the bridge response to the excitation of an approaching vehicle on road is utilized to evaluate the transmissibility of the road-soil-abutmentbridge (r-s-a-b) path. By comparing the FFT spectrums of bridge acceleration responses before and upon a vehicle traversing over an abutment, we found that the response spectrum consists of specific frequency of vehicle excitation, even though the bridge response before vehicle traversed over the abutment has a much smaller magnitude. This suggests that the bridge response before the vehicle traversed over the abutment is sensitive enough to be used to characterize the dynamic features of r-s-a-b transmissibility. Hilbert-Huang Transform method is used to extract the non-stationary information of the moving vehicle excitation from the bridge responses to characterize the r-s-ab transmissibility. It is found that specific signature associated with the specific frequency of vehicle excitation can be extracted from the Hilbert spectrum of empirical modal decomposition signals, and this signature could be readily quantified as a monitoring index which exhibits time-varying property.

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A method to identify optimal strain sensor placement for examining structural static responses is presented. The method is based on the use of numerical optimization. Based on an assumed set of applied static forces, the optimal sensor placement can be obtained, and the measured strains can be used to provide the information needed to describe the structural stiffness. For example, the cross-sectional area can be determined by minimizing the difference between the analytical and measured strains. This approach is used to identify the optimized sensor placement. The objective of this study is to identify the minimum number of static strain sensors and the optimal sensor layout needed to evaluate a bridge's structural condition. This study includes an automatic model parameter identification method, optimal static strain sensor placement, damage detection, and application to an actual bridge.