Condition Assessment Of Long-Span Prestressed Concrete Continuous Girder Bridges Based On Monitoring Data

Large bridge construction has made remarkable achievements in our country. However, the collapses of some bridges have brought immeasurable losses to the property of national economy and it also has caused a huge impact on the development of bridge industry. Therefore, in order to ensure the safe operation of large bridge structures and avoid the heavy casualties and property losses, a key issue is to clearly know the current condition of the bridge structure automatically and to find the potential safety hazard in time. As a consequence, the long-term health monitoring and safety condition assessment of large bridges is an urgent need to solve the problem of science and engineering in the construction of the national economy. It has important scientific significance and practical value.In order to study the reasons and variation of the mid-span of long-span PC continuous box-girder bridges with the stiffness reduction, three finite element models of continuous box girder bridges with different span length were developed. In addition, mid-span deflections of a finite element model of Fu Sui Bridge under the prestressed tendons reducing, reserved prestressed tendons tensioning, long-term shrinkage and creep and temperature variation were calculated. A long-term health monitoring system has implemented on Fu Sui Bridge. In the system, a comprehensive monitoring strategy was applied by using static leveling system to monitor displacement, using fiber Bragg grating sensors to monitor temperature, strain and acceleration. The overall structure, operation mode and the function of the subsystem in the system were also introduced.Due to the large number of data obtained from long-term monitoring, using the EMD method to separate the trend items in signal will consume a large amount of computational costs. A new method for separating trend items was proposed. In this method, "down sampling" process was applied to analyze the signal by using EMD method to obtain trend items. Then three-spline interpolation method was applied to reducing the length of trend term. Signal fitting method of exogenous input auto regressive moving average neural network model was established. The model was evaluated by the criteria of loss function, FPE, ACF and R2.Taking into account the existence of damage information in temperature trend signal, a structural damage identification method based on the combination of EMD and Markov distance was proposed. There were high correlation between the strain signal and temperature outside of the box. The temperature trend term signal and signal after deleting the trend term were obtained by using EMD method to separate the residual trend term in the strain response. The temperature trend term is fitted by the exogenous input auto regressive moving average neural network model to obtain the fitting. residuals of reference samples and measured samples. The vector of damage identification based on the Markov distance was constructed. The structure damage was identified by the signal after deleting the trend term and the fitting residual signal. The problem of damage information loss after separating trend term was effectively solved.An structural damage identification method based on covariance driven stochastic subspace and fault diagnosis technology was studied. The influential factors to the damage identification results including the value of θ, the size of Hankel matrix, environmental incentives and other factors were analyzed. According to the influence of temperature load on the vibration of concrete box girder bridges, the Hankel matrix and the null space model in different temperature ranges were established. The residual vectors in different temperature ranges were constructed. χ2 value calculated by the residual vector was used to identify the structure damage.According to the stress characteristics and load reference period in the operation stage of concrete box girder bridge, an reliability evaluation method of concrete continuous box girder bridge based on SHM monitoring data was proposed. The composition of the strain response and reference period of different various loads in long term monitoring data were analyzed. The vehicle load response and temperature gradient load response were extracted to fit the probability density. The limit state equation of concrete continuous box girder bridge under normal use limit state was established based on the day of reference period. The probability density function fitted by the vehicle load response and the temperature gradient load response were changed to equivalent normal state by using JC method. The reliability index and failure probability of continuous box beam monitoring section were calculated.Based on the data obtained from the long-term monitoring system of Fu Sui bridge, changing rules of vehicle load response and temperature load response was analyzed. The dynamic characteristics of concrete box girder bridges were analyzed by using Fourier transform and Hilbert-Huang transform. Fu sui bridge status were assessed by using the reliability method based on monitoring data.