The Intelligent Early Warning Monitoring And Numerical Simulation Research Of Deep Foundation Pit

Beijing is the earliest city to build a subway in China,which was built in 1966and operated in 1971.So far,there are 35 cities in China that have opened subways.The total mileage of operation is about 5,000 kilometers.In 2020,the mileage of China's subway will reach 6,000 kilometers.The construction of the subway is an important means to solve the current urban traffic problems.In the construction of subway engineering,because most metro stations are located in the central part of the city with dense buildings and complex pipelines,how to ensure the stability of the foundation pit during excavation has always been an important topic for many scholars.In order to ensure the safety of the foundation pit engineering,automatic monitoring technology has developed rapidly in recent years.The automatic monitoring technology is more accurate and convenient in the foundation pit deformation monitoring than traditional manual monitoring.Therefore,many deep and large foundation pits adopt automatic monitoring technology.With the advancement of computer hardware and software technology,numerical simulation method has become one of the important methods for deformation analysis of deep foundation pits.According to the survey results,the prediction of foundation pit deformation through simulation can provide reference for foundation pit design.This article relies on the deep foundation pit project of Dingxi Road Station of Lanzhou Metro Line 2.The foundation pit was comprehensively monitored through the development of a reasonable monitoring plan.In some sections,automatic monitoring technology was introduced to realize intelligent monitoring and early warning of foundation pits.The simulation of the fluid-solid coupling model of the foundation pit uses the finite difference software FLAC^3D.According to the monitoring and simulation results of the foundation pit,the change law of the two is compared and analyzed.The results show that the deformation of the foundation pit is consistent with the variation of the depth and time of the foundation pit under two conditions.The amount of deformation of the monitoring and simulation results is also basically consistent,and both are less than the warning values.The BP neural network in MATLAB is used to invert the soil parameters.The parameters of the inversion are input into the numerical model for simulation calculation.The corrected numerical results are closer to the actual deformation of the foundation pit,and the deformation of the foundation pit is predicted more accurately.The research content of this thesis is as follows:?1?According to the site conditions,a reasonable monitoring plan has been formulated.Some monitoring projects introduced automatic monitoring equipment and completed intelligent monitoring of foundation pits;?2?Using the finite difference software FLAC^3D,a three-dimensional numerical model is established based on geotechnical engineering investigation report and related parameters of foundation pit design,and the application of FLAC^3D in simulating foundation pit dewatering is also studied;?3?On-site monitoring data of foundation pit,the deformation law of foundation settlement and maintenance structure of foundation pit is analyzed.The accuracy of the numerical model is evaluated by comparative analysis of numerical simulation results and monitoring data;?4?The orthogonal experiment was designed with the soil parameters as variables.Combining the actual monitoring data on site,the BP neural network is used to invert the parameters of the FLAC^3D numerical model;?5?A multi-parameter automatic warning has been implemented.The intelligent early warning monitoring and numerical simulation research of deep foundation pit was completed.