This paper is meant to accurately obtain the particle size distribution of coal dust on fully mechanized excavation face of coal roadways and proposes an optimization scheme based on a genetic al-gorithm for particle size distribution.The study works by measuring the particle size of coal dust using the microscopic imaging method to obtain the number density distribution data of dust particles,establishing an optimization model based on Gaussian,log-normal,and Rosin-Rammler distribution functions and sol-ving it by using the optimized genetic algorithm,which is verified with the measured numerial values.The results indicate that the optimized genetic algorithm with 140 generations,a population size of 1 400,a crossover probability of 0.65,a mutation probability of 0.055,40 stall generations,a function toler-ance of 10-5,and a constraint tolerance of 10-4,exhibits good stability in problem-solving,and accu-rately and quickly determine the optimal parameter values with the three distribution functions matched.The goodness-of-fit R2 values are 0.801 for the Gaussian distribution,0.798 for the log-normal distribu-tion,and 0.839 for the Rosin-Rammler distribution.The Rosin-Rammler distribution function had the highest R2,indicating the best fit with the measured data,and this particle size distribution of the coal dust conforms best to the Rosin-Rammler distribution.
关键词
煤粉/遗传算法/颗粒粒径/粒度分布优化
Key words
pulverized coal/genetic algorithm/particle size/optimization of particle size distribu-tion
维普
万方数据