Adaptive Genetic Algorithm Based Combination Analysis Of The Influence Factors To Coal Spontaneous Combustion Period

The spontaneous combustion of coal seam is one of the major calamities in safe production of coal mine. And the spontaneous combustion period is the most direct and most extensive used key parameter. So it has great importance and significance to study the influence factors to coal spontaneous combustion period. This paper analyzed the main influence factors to coal spontaneous combustion period by different experiments focusing on macroscopical characteristic parameters, characteristic temperatures and microcosmic active groups. Firstly the changing rule of characteristic temperature of coal by Thermogravimetric Analysis is discussed, the rule of particle size and oxygen density influences to coal ignition process is given, and the critical oxygen density is measured at about 13%. Then the active function group character at different steps is classified and analysed, which show that under 150 centigrate the hydroxide, sub-cymene and carbon double bond,etc are the main reactant of coal self ignition. And through programmed heating experiment, oxygen consuming velocity, carbon monoxide producing velocity, carbon dioxide producing velocity, etc, the maximum and minimum exothermic intensity and the characteristic exothermic intensity are surveyed, also particle size influence is discussed, and critical temperature of coal sample in different areas is contrasted, which all falls in the scope of 50~80 centigrate. Based on the experiment results achieved, this paper tries to build up the rational connection between coal spontaneous combustion period and the main influnece factors by combination analysis method. The fixed relationship of coal particle size, intespace ratio, wind supply capacity, initialization temperature, characteristic exothermic intensity and spontaneous combustion period is established by multi-parameter Regression Model, Grey Model,or GM(0,5) and Neural Network Model, which provides a real approach to study coal self ignition. Then, Genetic Algorithm based Combination Analysis Model is realized to reduce the insufficient accuracy of sole analysis model. At the end of this paper, the experiment data of ShuangYaShan DongRong Second Mine and Third Mine is presented as samples to test different models established above, results show that combination analysis model can reflect the relationship of influence factors to spontaneous combustion period.