Study On Wireless Monitoring And Early Warning Technology Of Coal Spontaneous Combustion In Qinglong Coal Mine

As one of the major disasters restricting the safe production of coal,coal spontaneous combustion has always been a problem that coal enterprises need to face from time to time.Therefore,the adoption of scientific and effective coal spontaneous combustion prediction and forecast technology is an important prerequisite for ensuring the safe production of coal mines.Traditional downhole prediction and forecasting methods have the disadvantages of single index parameters,long laying distance,easy to block and leak gas beams,and easy damage to optical fiber lines.In view of the above problems,this paper takes 11811 goaf of Qinglong Coal Mine as the research object adopts a combination of coal spontaneous combustion index gas experiment,GA-BP goaf temperature prediction model,and field application research method to monitor the spontaneous combustion of goaf coal.Early warning technology has been systematically studied,which is of great significance to realize the monitoring and early warning of coal spontaneous combustion disasters in goafs.Through the 16#,17#and 18#coal seam coal sample temperature-programming experiments in Qinglong Coal Mine,the analysis of the change law of each gas with temperature is summarized and analyzed to determine the early warning gas and characteristic temperature of coal spontaneous combustion and to classify the early warning level of coal seam natural degree.The concentration of the underground monitoring and early warning uas index is selected as the input layer of the model,and the output target is the predicted coal temperature.The genetic algorithm is used to optimize the BP neural network to construct the GA-BP goaf temperature prediction model.Through error analysis of the model,the optimal temperature prature prediction model for goaf is selected.Constructed a coal spontaneous combustion wireless monitoring and early waming device,base station and system integrating O2.CO,CH4,pressure differrence and other sensors,and developed goaf monitoring and early warning software,which can realize online real-time monitoring,coal spontaneous combustion early warning and historical data trend analysis And other functions.The system is applied to the 11811 goaf of Qinglong Coal Mine.Through on-site monitoring data and manual chromatographic error analysis,the results show that the system can achieve the expected set indicators,and the data can be transmitted to the ground PC control terminal in a timely and accurate manner for easy management Personnel monitoring and early warning have achieved early prevention and control of coal spontaneous combustion disasters in the goaf.