Research On The Method For Predicting Of Coal Mine Pressure Based On Spatiotemporal Correlation Analysis And Probability Estimation Of Incoming Pressure

China is very rich in coal resources,but the mining conditions are not ideal.Coal safety accidents occur from time to time,among which the roof accident ranks first in the hazards of various coal mine accidents in our country.Coal mine pressure prediction of working face is an important means of early warning of roof disasters,and it is of great significance to ensure safe,economical and efficient mining of coal mines.There are two problems in the existing coal mine pressure prediction methods:①There is no in-depth analysis of the spatiotemporal correlation among the mine pressure data when constructing the training sample set.②In some moments,the predicted value of mine pressure has great deviation.These problems seriously affect the improvement of prediction accuracy.In order to achieve high-precision mine pressure prediction of coal mining face,this paper mainly does the following work:Firstly,a sample set construction method based on spatiotemporal correlation analysis is proposed.First,based on the grey correlation degree,the spatiotemporal correlation analysis of the rock pressure data is carried out,and the optimal time window and the closely related hydraulic support group are identified.Secondly,a training sample set is constructed according to the results of the spatiotemporal correlation analysis,and the LSTM prediction model is trained.Finally,the prediction model is evaluated with the mean absolute error as the evaluation index.The experimental results show that,compared with the traditional LSTM model,the prediction error of the LSTM model constructed by this method is reduced by 4.3%on average.Secondly,an approach probability estimation method based on conditional entropy is proposed to predict the approach probability of the working face.First,the original rock pressure data is divided into pressure to generate a series of pressure state.Second,the optimal historical state condition number is calculated based on the conditional entropy.Third,the best historical state condition number is found out,and the probability prediction tree is constructed.Finally,according to the probability prediction tree,the probability prediction of the working face is realized.Thirdly,a method for revising coal mine pressure prediction based on probability estimation of incoming pressure is proposed,which uses the prediction result of the probability of arrival to revise the prediction result of the spatiotemporal correlation analysis.For a certain moment in the future,the prediction of the mine pressure and the probability of the coming pressure are carried out at the same time.When the two prediction results are contradictory,the expected value of the mine pressure is calculated as the final predicted value of the mine pressure,so as to correct the prediction result.The experimental results show that,compared with the spatiotemporal correlation analysis method,the prediction error of this method is reduced by 4.1%on average.Finally,on the basis of the previous research,a characteristic analysis and prediction system of rock pressure in coal mining face is designed and developed.The system realizes the features of rock pressure analysis and prediction,and visually displays the operation results.