| Dynamic deflection of long-span bridges is an important index for safety,durability analysis and damage diagnosis.The dynamic deflection data obtained by the monitoring system is the result of the combined action of many factors.The factors causing the change of bridge deflection can be divided into vehicle load,temperature,prestress loss and concrete shrinkage creep,etc.Based on the National Natural Science Foundation of China(51408452)and the Hubei Provincial Key Laboratory Open Fund Project(DQJJ201709),the dynamic deflection data of the bridge collected by the bridge safety monitoring system based on Beidou satellite are separated,and the contribution value of each single factor deflection is obtained accurately,which provides the conditions for the evaluation of the working performance and damage diagnosis of the bridge.All the research works and conclusions are as follows.(1)The approaches using the multi-scale processing method,analyzing the effect of various factors on the time scale are applied and the deflection signals are classified.Aiming at the vehicle load deflection which belongs to the high frequency signal component in the deflection signal,the moving average filter is used to separate it.The temperature effect and long-term deflection belong to the low frequency signal and the frequency between the deflection components is too close,and the general signal processing method is difficult to achieve the separation.Blind source separation can also separate the source signal well under the condition that the frequency difference of the source signal is small and the frequency is mixed,but the number of observed signals must be greater than or equal to the number of source signals.The Ensemble Empirical Mode Decomposition(EEMD)has good adaptability,which can decompose the mixed signals of single channel into multi-scale and form multi-channel signal,but the decomposition result has the endpoint effect and the modal aliasing.The paper has a complementary advantage in using two algorithms,puting forward a new method based on the combination of the EEMD and blind source separation to separate the low frequency components in the deflection signal of the bridge.In the process of separation,the self-adaptability of the algorithm is enhanced by the application of source number estimation and false component recognition.(2)With the model of background bridge established by the finite element software Midas/civil,the response of the bridge structure under the action of each single factor is obtained and it is superimposed together as a mixed deflection signal to be separated.The correlation coefficient between the result of the simulation signal separation and the source signal is above 0.95,and the separation effect is better.The Beidou satellite-based bridge safety monitoring system is used to collect the deflection signal for one year in the symmetrical position of the main span,and then the separation deflection signal is separated by the separation method proposed in this paper.After separation,the correlation coefficient between the correlation coefficient of temperature effect and long-term deflection is more than 0.9,indicating that the separation effect is better.(3)For the large amount of deflection data obtained by long-term monitoring,the temperature effect in the deflection signal of the bridge is separated by the method based on the combination of eemd and blind source separation,and then the data after removing the temperature effect is used in the damage diagnosis of the structure.The diagnosis method of statistical process control based on X control graph is adopted to realize the preliminary diagnosis of bridge health condition.Then using the diagnosis method based on Markov distance cumulative vector to further determin the damage degree and damage location,and the damage diagnosis of the bridge is finally realized.The validity of this method is verified by numerical simulation and actual engineering bridge deflection monitoring data. |
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