Reform Of Health Monitoring System Of Heichonggou Bridge And Analysis And Prediction Of Monitoring Data

With the continuous development of my country’s transportation industry,the number of bridges,as key nodes of the transportation network,continues to increase,and the bridge structure becomes more and more complex.During the long-term service,bridges are affected by problems such as load effects,external environment,and internal material aging.As a result,bridges are damaged to varying degrees,and the safety of bridges has also received extensive attention.Through the construction of the bridge health monitoring system,it is crucial to grasp the bridge’s own structural information and external environmental conditions in a timely manner,so as to evaluate the bridge operation status,find problems in time,and take effective measures to prevent them.Taking the Heichonggou Bridge as the engineering background,this paper studies the health monitoring system of the bridge from the aspects of system design,instrument selection,data processing and analysis.Firstly,according to the structural characteristics of the Heichonggou Bridge,the operation of the original health monitoring system and environmental factors,the health monitoring system was reconstructed.The reconstruction design of the system includes the overall design and subsystem design.Data acquisition and transmission subsystem,data processing and management subsystem,structural safety assessment and early warning subsystem and bridge monitoring platform,through the comparison and selection of various instruments and equipment,select appropriate sensors;secondly,use MATLAB software programming to analyze the health monitoring data.Perform outlier elimination,data smoothing and normalization processing,qualitatively analyze the processed temperature and strain trend graphs,and then use Grey system theory to perform Grey correlation analysis on the preprocessing temperature data and strain data.The Grey correlation degree between the strains of each measuring point is above 0.8.Through qualitative analysis and quantitative analysis of the Grey correlation degree,it is found that temperature has an important influence on the strain.Finally,taking the temperature of the measuring point and the difference of sunshine temperature as the explanatory variables,and the strain as the response variable,a multiple linear regression model and a BP neural network model were established to fit and predict the strain,and the goodness of fit and prediction accuracy of the two models were compared.Through the transformation design and data analysis and prediction of the health monitoring system of the Heichonggou Bridge,it can provide corresponding data support for the subsequent maintenance and management of the bridge,and provide a corresponding method for the prediction of the bridge structure response,which is of great significance to the operation and maintenance of the bridge.actual engineering value.