Multi-factor dynamic analysis of the deformation of a coal bunker in a coal preparation plant

To assess the deformation of a coal bunker and propose effective preventative measures for such,a real-time monitoring system was designed.Moreover,methods were proposed for monitoring the coal-bunker inclination,settlement,groundwater level,temperature,and material level.By using a vector autoregression model and time-series data for the coal-bunker deformation,a long-term equilibrium relationship was derived between the coal-bunker inclination and settlement and their influencing factors.The dynamic effects of each factor on the coal-bunker inclination and settlement and how the contribution of each factor changes were revealed by using an impulse response function and variance decomposition.The results show that the coal-bunker inclination and settlement vary hysteretically.Groundwater level has constant and small negative effects on the coal-bunker inclination and settlement,and temperature has continuous and significant negative effects;however,material level has constant positive effects on the coal-bunker settlement and slightly influences the eastward inclination while significantly influencing the northward inclination of the coal bunker.Also,unbalanced loading has little influence on the coal-bunker settlement and eastward inclination but significant influence on its northward inclination.Therefore,monitoring of the coal-bunker deformation should be strengthened in summer,and sudden changes in material level and unbalanced loading should be avoided during production.Moreover,the coal-bunker inclination can be adjusted by unbalanced loading in the reverse direction.

Dynamic capacity balance between stripping and mining of a dragline stripping system

The reliability factors of a dragline stripping system were analyzed using system reliability theory to improve its reliability and ensure the stability of surface coal mine production.The relationship between the dragline scheduled stripping volume with both the weighted average thickness of the coal seam and the height of the blast casting bench was derived.The results show that the reliability of the dragline stripping system decreases with the weighted average thickness of the coal seam and increases with a reduced casting blast bench height and monthly raw coal production capacity.Furthermore,the dynamic monthly advance distance of the dragline stripping system was found,a new concept of the dragline stripping system reliability and measurement methodology were proposed,and a prediction model for the dragline production capacity was established using a generalized regression neural network.In addition,the steps and processes of the reliability were improved.The study on the Heidaigou surface mine shows that the height of the casting blast bench should be reduced to 10.5 m when its raw coal production capacity is improved from 20 to 30 Mt/a.During the normal production of surface coal,the system reliability can be improved by dynamically determining the weighted average coal seam thickness,accurately predicting the dragline production capacity,and taking other corresponding measures.