Study On Inversion Method Of Fire Source Position And Strength Based On Surface Temperature Of Loose Coal

Concealed fire refers to a fire caused by spontaneous combustion of coal oxidation and heat storage caused by air leakage in the goal or inside the coal wall of a coal mine.Concealed fires have the characteristics of strong concealment,deep location,large heat capacity and blindness in treatment.Secondly,spontaneous combustion will pose a serious threat to the safety of underground coal mine production and cause a lot of waste of coal resources.Therefore,how to detect concealed fires as early as possible and accurately locate the fire source at the early stage of the development of concealed fire sources to provide guidance for timely fire prevention is the key to the management of concealed fires in coal mines.Based on the characteristics of concealed fires in coal mines,build an active temperature test bench inside loose coal,restore and simulate the development process of hidden fire sources in coal mines,by changing the coal particle size to analyze the heat transfer law of the coal under different porosity conditions,and the changes in the internal temperature field of the coal body under different heat source intensity conditions,A simplified model of numerical simulation is used to analyze the influence of different thermal conductivity on the internal temperature field and the temperature change law of the natural convection surface on the upper surface of the coal body.A mathematical model of point heat source diffusion is established based on the heat transfer equation and the data obtained from experiments and numerical simulations.Using genetic algorithm to build inversion algorithm,the location and intensity of the fire source can be back calculated from the law of changes in the surface temperature of the coal body.The results show that the internal temperature field of the loose coal is centered on the heat source at the beginning of the experiment.The heat is conducted in a spherical shape to the surrounding coal body,when a steady-state convection heat transfer is formed between the internal temperature field and the natural convection surface on the upper surface.the internal temperature field is ellipsoidal,and the heat is mainly transferred to the upper surface.different heat source intensities have little influence on the transfer of the internal temperature field of the coal body;porosity is the main factor that affects the internal heat transfer of coal,when the porosity increases,the temperature rise of the internal temperature field increases,but the temperature rise of the natural convection surface decreases;The thermal conductivity has a greater impact on the heat transfer of the coal.The greater the thermal conductivity,the greater the heating rate of the coal,and the easier it is to observe the increase in the surface temperature of the coal.The mathematical model is established based on the point heat source diffusion equation.The strength and position of the heat source inside the coal body can be accurately inversed by genetic algorithm.The accelerated genetic algorithm is used to optimize it.By increasing the optimization range,the accelerated genetic algorithm avoids the model error caused by discretization and improves the inversion accuracy.The minimum temperature error is 0.003℃ and the minimum position error is 0.012 m.At the same time,the traditional genetic algorithm and the accelerated genetic algorithm are compared and analyzed to provide theoretical support for the detection,prediction and prevention of hidden fire sources in coal mines.