Prediction Technology of Roof and Floor Shape of Coal Seam in Intelligent Fully Mechanized Mining Face
The prediction of the undulation state of the roof and floor in fully mechanized mining face of coal mine is one of the key technologies for the intelligent mining.In order to solve the problem of large prediction error of roof and floor shape of coal seam,based on the basic principle of memory cutting technology of shearer,a prediction model of roof and floor shape of fully mechanized mining face based on Convolutional Long Short-Term Memory Network(CONV-LSTM)was constructed.Firstly,the shape features of the roof and floor were extracted using the spatial information of the strike of the regional shearer and the time information of the mining strike.Then,the CONV-LSTM model was constructed using the extracted shape features.Finally,the model was evaluated using the coal seam shape data of 5-20109 working face in Qinglongsi Coal Mine.The field test shows that the average prediction error of the roof shape is 3.5 cm,and the average prediction error of the floor shape is 5.8 cm.The results show that the CONV-LSTM model can realize the accurate prediction of the roof and floor shape,and meet the demand for the height adjustment of the front and rear drums of the shearer in the project,which is of great significance for realizing the intelligent mining of the fully mechanized mining face.
CONV-LSTMFully mechanized mining facePrediction of roof and floor shapeIntelligent mining
万方数据
维普
