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Summary: Modal frequencies are widely used for vibration‐based structural health monitoring (SHM) and for capturing the dynamics of a monitored structure to reveal possible failures. However, changing environmental and operational conditions (i.e., temperature, humidity, wind load, and traffic load) may submerge the modal variability induced by structural damage, thereby falsely identifying damage of interest. This paper presents a comprehensive summary review of SHM for the prediction of modal frequency and the elimination of environment‐induced masking effects based on the data normalization method. The influence mechanisms of external variations on modal frequencies extensively reported in the literature are first described. Next, the research progress in predicting and eliminating the operational modal variability is reviewed emphatically; this progress can be primarily divided into an input–output method that focuses on the establishment of the relationship model between structural frequency and environmental conditions and an output‐only method that separates the embedded environmental variable‐induced changes depending on whether the environmental measurements are measured. Finally, the conclusions and future studies are summarized and discussed. As an overview, the major contribution of this paper is to provide objective technical references for engineers and owners and to further evaluate structural safety conditions more effectively and in a timely manner. [ABSTRACT FROM AUTHOR]

Summary: As critical components that transmit internal forces laterally in multigirder bridges, joint degradation can destroy the cooperative working mechanism of a multigirder system and seriously reduce bridge bearing capacity. This research aims to reveal the joint damage effects on lateral internal force transmission and propose a joint damage detection and location method. A spring‐jointed plate model is established to analyze the effects of joint damage, based on which the relationship between the shear forces in the joints and the shear stiffness of the joints can be obtained. Furthermore, a joint damage index is deduced based on the lateral deflection influence lines, and a bridge load testing method is proposed to obtain such influence lines. By using multiple influence lines to jointly solve the damage index, the joint damage in the lateral bridge direction can be accurately detected and located. In addition, by carrying out the damage detection process at several cross sections of the bridge, the joint damage position in the longitudinal bridge direction can also be determined. Finally, a numerical model of an adjacent box girder bridge is illustrated as an example to verify the effectiveness of the damage detection. It can be concluded that the proposed method can effectively identify and locate single or multiple joint damage locations under noise interference, and the joint damage degree can be quantitatively evaluated. This study can provide an effective method to identify the joint damage for adjacent box girder bridges with high accuracy and reliability. [ABSTRACT FROM AUTHOR]

Summary: Bridge influence surface is an important tool to study the bridge responses under the moving loads, which contains tremendous structural information. The structural deterioration during the service life would induce the variation of the bridge influence surface, which makes it essential to identify the influence surface exactly from the field measured data under moving vehicle loads. This paper firstly summarizes current development of bridge influence surface identification methods and classifies the methods in which the vehicle is respectively equivalent to line loads and concentrated loads. After that, the actual spatial distribution of the vehicle load is considered, based on which a new identification method is presented to solve the boundary problem of current influence surface identification methods. Then a numerical slab model with two fixed ends is illustrated to prove the validity of the method, and the accuracy and identifiable region of different methods in this condition are compared with the other methods. Influence factors of identification accuracy including noise level, axle number of vehicle and loading point are analyzed. Finally, laboratory verification using the same slab model is prepared to verify the effectiveness of the proposed identification method. Results of this study provide an effective identification method of bridge influence surface with very high identification accuracy, which can be used to full bridge influence surface test. [ABSTRACT FROM AUTHOR]

Summary: The bridge influence line can reflect the structural behavior under moving vehicle loads, which is becoming a proposing tool to study the bridge behavior during service life. A high‐speed vehicle will induce dynamic effect on the bridge, which will significantly change the shape of response curve. It is essential to consider the dynamic response for the accurate identification of the bridge influence line. This paper firstly summarizes current research activities for bridge influence line identification and components of the bridge dynamic responses. A dynamic fluctuation part elimination method based on empirical mode decomposition is proposed, based on which the bridge static influence line is identified by static bridge influence line identification method. Finally, a vehicle–bridge coupling model of a simply supported beam excited by passing vehicles with three different speeds is introduced to illustrate the effectiveness of the proposed identification method. The result of this study provides an effective identification method of the bridge static influence line, which can lead to a satisfactory identification results based on the dynamic responses induced by high‐speed vehicle loads. [ABSTRACT FROM AUTHOR]

Summary: Sliding bearings of a bridge are important sliding elements that accommodate the bridge movement caused by temperature action and vehicle/wind load. The sliding life of sliding bearings is determined by the wear of the sliding materials in the bearing. However, the wear of sliding bearings primarily results from a large amount of cumulative sliding displacement experienced by the sliding bearing, even if the movement of the bridge under the vehicle/wind load is far less than the allowable design displacement of the sliding bearing. In general, bearing displacement is monitored using displacement gauges with a low sampling frequency, which cannot accurately capture the relatively high‐frequency displacement component caused by vehicle/wind loads. For predicting the sliding life of sliding bearings, this paper provides a mode rotation angle superposition approach to estimate cumulative sliding displacement. The estimation approach incorporates the combination of the rotation angles of bridge ends and the modal parameters of bridges. The feasibility and advantage of the estimation approach are illustrated by a numerical example; then, the influence factors of the error are analysed. Finally, sliding life prediction of sliding bearings is applied to an actual bridge using the estimation approach of cumulative sliding displacement. [ABSTRACT FROM AUTHOR]