Design And Implementation Of An Intelligent Monitoring System For Geological Disasters Based On Slope Radar

With the rapid development of information technology,communication technology and electronic technology,the prevention and control of geological hazards has attracted widespread attention from all walks of life.Related disaster prevention programs and products are constantly emerging.Meanwhile the slope radar with the characteristics of all-weather,high-precision and all coverage came into being.It is an important tool to realize surface deformation monitoring,fixed-point continuity monitoring and regional terrain monitoring.However,there is a large amount of random interference noise and local abnormal data in the original deformation monitoring data measured by the slope radar,at the same time,the data transmission and processing technology is not perfect.And it also has become one of the important problems of the geological disaster early warning system.Therefore,in view of the above problems,this paper develops a geological disaster monitoring system software platform with remote monitoring and intelligent processing capabilities based on the existing slope radar.In terms of intelligent data processing,according to the deformation information accumulated in the scene,the original deformation data is extracted.Due to the deformation measurement error in the original deformation data,the thermal noise error can be regarded as a Gaussian random variable,the atmospheric compensation error is time-varying,and the obedient error model is unknown.Therefore,a filtering method is needed to effectively remove the interference data.In this study,Kalman filter is adopted.The initial state is the deformation variables corresponding to the last image of the historical data.The Kalman filter state equation and observation equation are established.The Kalman equation is obtained through the estimation equation of the state mean square error matrix.Then the filtered gain equation is corrected for the state estimation equation,and finally the mean square error equation is updated.In this way,accurate deformation variables are extracted.At the same time,the accuracy and effectiveness of this algorithm were simulated and verified using the measured data obtained from the deformation monitoring experiments carried out in the open-pit mining slope of Malanzhuang,Qian’an City,Hebei Province.In terms of geological hazard monitoring and early warning software,in order to achieve real-time display and processing of data,this study uses Microsoft Visual Studio 2010 as the design and development platform,uses the object-oriented C # programming language mixed programming with MATLAB 2012 b,is based on a multi-threaded transaction model,and designs the software architecture in layers.The original deformation data is transmitted to the upper computer through the wire communication network,and the parameters are transferred.At the same time,the function of each module is designed according to the demand analysis.The Graphical User Interface(GUI)module realizes the human-machine interaction.The control module realizes the scheduling of algorithm,network connection and synchronization of execution thread.The logic function module realizes the extraction of deformation data,deformation filtering,data storage,etc.The data transmission module adopts TCP/IP protocol and realizes the encapsulation of Socket.