Personnel safety guarantee under pressure prediction of hydraulic support in fully mechanized mining face
The change of the hydraulic support pressure in the working face area can lead to the change of the safety situation in the support associated area.Predicting the change of support pressure values in advance can prevent the corresponding accidents to a certain extent.The paper focused on the research of personnel safety guarantee method under the support of coal mine working face.According to the prediction results of support pressure and personnel trajectory,the personnel whose moving trajectory may pass through the dangerous support position were reminded in advance,so as to improve the safety guarantee level of workers in the working face area.Firstly,a mine pressure value of the support groups prediction algorithm based on AMG-TSMixer was proposed.The AMG algorithm was used to fully exca-vate the spatial-temporal relationship of different supports in the same working face,and TSMixer was used to predict the mine pressure value of the support groups.Combined with the existing mine pres-sure monitoring and early warning system and method,the safety state of the support area was analyzed in advance.Secondly,a personnel trajectory prediction algorithm based on the GRU-Transformer net-work was proposed,which captures spatial-temporal features through the GRU network,thereby enhan-cing the memory ability of the Transformer model and excavating the complex interaction relationships between personnel in more detail.Through the analysis and judgment results of personnel trajectory and support safety area,it provided future solutions for personnel safety guarantee.The results show that the proposed AMG-TSMixer method has improved by 5.9％and 10.7％compared with similar representa-tive methods in the two indicators of RMSE and MAPE,and can effectively predict the mine pressure value of the support groups;The proposed GRU-Transformer method in this paper has improved by 14％and 19％compared with similar representative methods in the two indicators of ADE and FDE,and can predict more realistic personnel trajectory.The results show that the proposed AMG-TSMixer method has improved by 5.9％and 10.7％compared with similar representative methods in terms of RMSE and MAPE.The proposed GRU-Transformer method in this paper has improved by 14％and 19％compared with similar representative methods in the two indicators of ADE and FDE.The combi-nation of the pressure value prediction of the support group and the personnel trajectory prediction method can not only effectively predict the pressure value of the support group,but also predict a more realistic personnel trajectory,which plays an important role in the safety guarantee of the workers on the fully mechanized mining face of the coal mine.
support pressure predictionpersonnel trajectory predictionpersonnel safetyGRU-Trans-former
万方数据
维普
