Design And Implementation Of Temperature Monitoring System For Spontaneous Combustion Coal Gangue Pile

Spontaneous combustion is a major problem in the treatment of coal gangue piles,and it often occurs due to the failure to predict the trend of internal temperature changes in a timely manner,making it difficult to take appropriate measures.Therefore,realtime temperature monitoring and timely prediction of coal gangue is crucial for effective treatment.The traditional manual inspection temperature measurement method for coal gangue piles has the disadvantages of a single monitoring method,low efficiency,and inability to monitor in real-time.The existing temperature prediction for the interior of coal gangue piles is generally based on certain linear laws to predict temperature in order to achieve early warning.However,the internal temperature of coal gangue piles often exhibits non-linear changes,which can result in low accuracy of temperature prediction.In response to the above problems,this thesis designs a temperature monitoring system for spontaneous combustion coal gangue piles.The system utilizes the UAV thermal infrared remote sensing and wireless temperature monitoring technology to comprehensively monitor the surface and internal temperatures of the gangue piles.In addition,the GA-BP neural network model is built to predict the internal temperature of the coal gangue piles.The main work of this thesis is as follows:(1)Construction of temperature prediction model for spontaneous combustion coal gangue piles.Based on the non-linear characteristics of temperature inside coal gangue piles,this thesis employs BP neural network and genetic algorithm to construct a prediction model.The representative internal temperature data of coal gangue dump were selected as the research object and preprocessed.Using the preprocessed temperature data,the BP neural network and the BP neural network optimized by genetic algorithm are simulated for temperature prediction.The error results of the two models are compared and analyzed,and it is concluded that the temperature prediction model constructed by GA-BP neural network has higher prediction accuracy.(2)Design and implementation of temperature monitoring system for spontaneous combustion coal gangue piles.Firstly,the overall design of the system is carried out,including the analysis of the overall requirements of the system,the design of the overall framework of the system,and the design of the system functional modules.Then,the database is designed and the hardware involved in the system is selected.Finally,the visualization interface of the system is implemented.(3)Application of temperature monitoring system for spontaneous combustion coal gangue piles.The system utilizes UAV thermal infrared remote sensing technology to monitor the surface temperature of the coal gangue pile on site.The periodic distribution of surface temperature obtained is visualized and displayed on the system,assisting management personnel in decision-making and analysis.The system layout and monitoring node layout plan are designed based on the wireless temperature monitoring system.The system was tested on site with the coal gangue pile,and its reliability was verified with the system operating normally.