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The vertical deflection of the main girder on a cable-stayed bridge is a direct reflection of the vertical stiffness of bridge structure, which represents the comprehensive mechanical performance of cable-stayed bridge. Compared with the deflection caused by vehicles, the deflection caused by temperature is often more significant and the change frequency is very low, which is easy to extract from raw data, and can be used as an index to evaluate the state of cable-stayed bridge. To obtain the control value for recognizing the abnormal deflection, it is necessary to establish an accurate input-output relationship between temperature and temperature-induced deflection. However, because of the high-order nonlinear relationship between the temperature and the temperature-induced deflection, the traditional linear regression is not accurate enough in modeling this relationship. To establish a high-precision model for the deflection, this paper uses the machine learning tools with the highly nonlinear fitting performance to further model the project. Considering both the precision and modeling efficiency, the Long-Short Term Memory (LSTM) network can build the optimal model between temperature and temperature-induced deflection. Use the regression value output by LSTM as the control value combining with the statistical pattern of t-test, the 6% abnormal deflection can be recognized. The 6% sensitivity can help to recognize bridge abnormalities earlier. &nbsp

To accurately evaluate the influence of the actual tension and compression state and stress ratio at the deck-to-rib welding seam position on the fatigue life of a bridge deck, this paper establishes a coupled stress analysis model that considers the welding residual stress and vehicle stress. Taking the Jiangyin Bridge as an example, a qualitative analysis of the fatigue life under the vehicle load and residual stress field is carried out using the proposed method. A case analysis showed that when the residual tensile stress in the welding seam position is superimposed on the mainly tensile cyclic vehicle load stress, the longitudinal stress relaxation exceeds the peak vehicle load stress; significant longitudinal stress relaxation occurred, while the transverse stress relaxation is not significant. However, when the residual tensile stress is superimposed on the mainly compressive cyclic vehicle load stress, the relaxations of both the longitudinal and transverse stresses are not obvious. Compared with the stress state of the welding point under the action of only the vehicle stress, when the coupling effect of the residual stress and vehicle stress is considered, i.e., the loading condition, the fatigue stress state of the weld point has undergone an essential change under cyclic compressive stress, that is, the compressive stress state that does not require a fatigue check is changed to the tensile stress state. Although the fatigue state of the tensile stress cycle condition has not changed, the fatigue life is reduced by varying degrees under either the compressive or tensile condition.

Bridge bearings experience numerous small-amplitude displacements under environmental loads. The continuous cyclic accumulations of these small-amplitude displacements will result in severe wear on the poly-tetra-fluoro-ethylene (PTFE) plates in the bridge bearings, which seriously endangers the service life of bearings. Traditional method directly uses the linear wear rate of cumulative displacements in a short period to evaluate the wearing life, but the linear wear rate only in a short period such as several days may not represent the characteristics in the whole bridge service life. Hence, this research takes the spherical steel bearings of the Nanjing Dashengguan Yangtze River Bridge as a study object. The cumulative dynamic displacement (CDD) under the action of a single train and the cumulative bearing travel (CBT) under the continual actions of many trains are studied using the monitored longitudinal displacement data from spherical steel bearings. Furthermore, the probability statistics and the Monte Carlo sampling simulation for CDD are studied, and the safety evaluation method for bearing wear life in the real environment is proposed using a reliability index regarding the failure probability of monitored CBT over the wear limit during service lifetime. In addition, safety evaluation on the bearing wear life was performed to assess the condition of spherical steel bearings in the real service environment. The results can provide an important reference for analysis on the bearing wear life of long-span railway bridge structures.

The wind-resistant performance of existing long-span cable-stayed bridge structures will inevitably deteriorate due to concrete carbonation, reinforcement corrosion, accumulated fatigue damage, etc., which can threaten the entire bridge safety. However, few studies currently focus on assessing the wind-resistant performance of existing long-span cable-stayed bridge structures, and at present, no studies have revealed how to identify the deterioration of the wind-resistant performance using a bridge health-monitoring technique. Therefore, based on the health-monitoring system installed on the Sutong Cable-stayed Bridge, the monitoring wind field and GPS displacement are captured to analyze the wind-resistant performance. First, the correlation between static cross wind and transversal displacement is analyzed, which is nearly linear but also contains discrete points caused by environmental noise. Second, considering that the discrete points can decrease the identification accuracy, one new method called the cross-correlation analysis of wavelet packet coefficients is put forward to effectively remove the discrete points. Third, considering that the traditional function cannot match the monitoring correlation very well, some new fitting functions are thoroughly studied to determine the best function for fitting the monitoring correlation. Fourth, the abnormal variation in the monitoring correlation caused by a deterioration in the wind-resistant performance is studied, and the root-mean-square (RMS) variable, which represents the difference between a good service state and a deteriorated service state, is used as a detection indicator to identify the deterioration of wind-resistant performance. Finally, the monitoring data from ten months are selected to evaluate the wind-resistant performance of the Sutong Bridge, and the result shows that its wind-resistant performance was still in a good service state during these ten months.

Fatigue has become critical issue for bridge with orthotropic steel deck. Number of stress cycle and equivalent stress amplitude were adopted as two investigated fatigue effects. As presented from fatigue monitoring comparison of two series-lined bridges, three local geometric parameters of steel box girder have significant influence on fatigue performance of two welded joints. They are thickness of longitudinal ribs (Tr), longitudinal spacing of transverse floor plate (Sc) and longitudinal truss (LT). Fatigue analytical models were created for parametric study of fatigue effects under wheel load. Consequently, three local parameters have exhibited insignificant influence on number of stress cycle. Compared with Tr and Sc, configuration of LT has brought about foremost effect on the equivalent stress amplitude. For equivalent stress amplitude of rib-to-deck and rib-to-rib welded joints, the influence regions of LT are respectively longitudinal strap and quadrate with the geometric length of 600 mm. Enough attention ought to be paid for local stiffen structure on fatigue performance of orthotropic steel deck in fatigue design and monitoring.

Damage alarming and safety evaluation using long-term monitoring data is an area of significant research activity for long-span bridges. In order to extend the research in this field, the damage alarming technique for bridge expansion joints based on long-term monitoring data was developed. The effects of environmental factors on the expansion joint displacement were analyzed. Multiple linear regression models were obtained to describe the correlation between displacements and the dominant environmental factors. The damage alarming index was defined based on the multiple regression models. At last, the X-bar control chart was utilized to detect the abnormal change of the displacements. Analysis results reveal that temperature and traffic condition are the dominant environmental factors to influence the displacement. When the confidence level of X-bar control chart is set to be 0.003, the false-positive indications of damage can be avoided. The damage sensitivity analysis shows that the proper X-bar control chart can detect 0.1 cm damage-induced change of the expansion joint displacement. It is reasonably believed that the proposed technique is robust against false-positive indication of damage and suitable to alarm the possible future damage of the expansion joints.

The driving security of trains at high speeds is among the pivotal issues significantly affected by the smoothness of rail lines. For high-speed railway steel bridges, the fatigue cracking of typical positions under the rail lines will reduce the stiffness of the deck plate, inducing the smoothing of the rail lines. In this paper, a new theoretical approach is proposed that integrates the fatigue assessment of a typical welded joint for high-speed railway steel bridges in service. Based on the strain history data recorded by a structural health monitoring system, the theoretical approach includes various factors, including stress concentration, environmental corrosion, and train flow. Upon application in an actual high-speed railway bridge with an orthotropic steel deck, the approach was used to conduct determinative and reliable fatigue-life evaluation of the bridge. A static-load experiment was conducted to obtain the stress distribution around the weld and the difference in stress between the p...

Making use of long-term transverse vibration monitoring data of DaShengGuan Bridge, the early-warning method of train running safety of the high-speed railway bridge is established by adopting principal component analysis (PCA) method. Firstly, the root mean square (RMS) of the transverse acceleration of the main girder is used as the monitoring parameter for the train running safety. The correlation model between the RMS values measured from different positions is further adopted as the evaluating model for the train running safety. Finally, the effects of the environmental changes on the evaluating model are eliminated using the PCA method and the warning index for the train running safety is further constructed. The analysis results show that the correlation between the RMS values of the accelerations from different measuring positions on the main girder can be analyzed by a quadratic polynomial fitting model. The PCA method can effectively remove the environmental effects on the quadratic polynomial fitting model. The proposed warning method provides a good capability for detecting the abnormal changes of the measured transverse accelerations and hence it is suitable for early-warning of the train running safety.

Taking advantage of the structural health monitoring system installed on the steel truss arch girder of Dashengguan Yangtze Bridge, the temperature field data and static strain data are collected and analyzed for the static performance assessment of the bridge. Through analysis, it is found that the static strain changes are mainly caused by temperature field (temperature and temperature difference) and train. After the train-induced static strains are removed, the correlation between the remaining static strains and the temperature field shows apparent linear characteristics, which can be mathematically modeled for the description of static performance. Therefore, multivariate linear regression function combined with principal component analysis is introduced to mathematically model the correlation. Furthermore, the residual static strains of mathematical model are adopted as assessment indicator and three kinds of degradation regulations of static performance are obtained after simulation of the residual static strains. Finally, it is concluded that the static performance of Dashengguan Yangtze Bridge was in a good condition during that period.

Based on the health monitoring system installed on the main span of Sutong Cable-Stayed Bridge, GPS displacement and wind field are real-time monitored and analyzed. According to analytical results, apparent nonlinear correlation with certain discreteness exists between lateral static girder displacement and lateral static wind velocity; thus time series of lateral static girder displacement are decomposed into nonlinear correlation term and discreteness term, nonlinear correlation term of which is mathematically modeled by third-order Fourier series with intervention of lateral static wind velocity and discreteness term of which is mathematically modeled by the combined models of ARMA(7,4)and EGARCH(2,1). Additionally, stable power spectrum density exists in time series of lateral dynamic girder displacement, which can be well described by the fourth-order Gaussian series; thus time series of lateral dynamic girder displacement are mathematically modeled by harmonic superposition function. By comparison and verification between simulative and monitoring lateral girder displacements from September 1 to September 3, the presented mathematical models are effective to simulate time series of lateral girder displacement from main girder of Sutong Cable-Stayed Bridge.