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.

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.

The Chulitna River Bridge is a 790-ft five girder, five-span steel bridge on the Parks Highway between Fairbanks and Anchorage, Alaska. This bridge was built in 1970 and widened in 1993. Under the no-live load condition, five support bearings are not in contact. Heavily loaded trucks often travel across this bridge to the oil fields in Prudhoe Bay, Alaska. A virtual finite element modeling, dynamic field testing of the “ambient vibrational response,” and structural health monitoring system are used to analyze, evaluate, and monitor the structural performance. As the first stage of the research, this article presents results from the dynamic testing and evaluation of the structural responses of the bridge. In the dynamic field testing, 15 portable accelerometers were placed on centerline along the bridge length to record the structural response, and an ambient free-decay response was used to evaluate the dynamic properties of the bridge structure. Natural frequencies and modal damping ratios were identified and characterized using Hilbert–Huang transform and fast Fourier transform methods. Compared with conventional approaches, this study demonstrates that (1) the Hilbert–Huang method was found to be effective and suitable for modal parameter identification of a long steel girder bridge using ambient truck loading; (2) the nonlinear damping was, for the first time, identified based on Hilbert–Huang transform’s amplitude–time slope; (3) modal frequencies are very sensitive to sensor location so their position should be optimized.

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As all bridges get deteriorated over time, structural health monitoring of these structures has become very important for the damage identification and maintenance work. Evaluating a bridge's health condition requires the testing of a variety of physical quantities including bridge dynamic responses and the evaluation of the functions of varied bridge subsystems. In this study, both the acceleration of the deck and the dynamic rotational angle of the bearings in a long-span steel girder bridge were measured when the bridge system was excited by passing-by vehicles. e nonstationary dynamical phenomena including vibration mode interactions and coupling are observed in response spectrogram. To elaborate the phenomena, the linear vibration mode properties of the bridge are characterized by finite element analysis and are correlated with the specific modes in test. A theoretical model is presented showing the mechanism of the mode coupling and instability originated from the friction effects in bearing.is study offers some insights into the correlation between complex bridge vibrations and the bearing effects, which lays a foundation for the in situ health monitoring of bridge bearing by using dynamical testing.