Total Kalman Filter Optimization Method For Mine Buildings And Structures Deformation Monitoring Data

Mine buildings and structures monitoring is an important content to ensure the safety of mining production facilities.Kalman filter can process real-time dynamic monitoring data and make predictions,when estimating the state parameters,the predicted value of the state equation is used as the prior information of estimated parameter,and the optimal solution is obtained by the least squares method.Based on the current state of Kalman filter equation and total Kalman filter,this paper works on the analysis of filter equation and solution of filter gain.Through summarizing the state vectors,observation vectors and control vectors involved in the fields of integrated navigation,GNSS dynamic positioning,deformation monitoring,the buildings and structures monitoring,the establishment of the state vectors,observation vectors and control vectors for deformation monitoring of mine buildings and structures are analyzed and suggestions are given.The total Kalman filter is described as an optimization problem and the iterative solution algorithm of the filter gain is derived by the total least squares method.Then comparing the Kalman filter and the total Kalman filter by the solution process of the filter gain matrix.The principle of algorithm of the total Kalman filter is analyzed,then combing the algorithm flow,and the gain matrix solution is discussed in detail.The program implementation of the total Kalman filter is divided into five parts: data preprocessing,parameter setting,initialization array and list,algorithm process implementation and filtering result analysis.The data structure and the global variable initialization function,cofactor matrix,gain matrix and the Kronecker product calculation method module are defined by Python language in order to implement the total Kalman filter algorithm.A calculation example is carried out through taking the support column of the coal cleaning plant as the experimental object.The Kalman filter and total Kalman filter are used to compare and analyze the filter results of displacement and velocity state parameters of the monitoring points.It shows that the total Kalman filter has some practical value in the processing of mine buildings and structures deformation monitoring data.