【摘要】 针对入选原煤煤层复杂多变、品种繁多，配煤计算复杂，劳动强度大，生产效率低等问题，骆驼山洗煤厂通过建立数学模型，采用专业数学计算软件——MATLAB编写粒子群优化算法(PSO)程序，根据入选煤的性质预测产品的数质量和分选工艺参数，对多煤种进行了炼焦煤配洗寻优计算，以快速、准确地计算出最优配煤比例并获得参考洗选参数。结果表明：在保证精煤指标的前提下，多煤层复杂煤质配洗入选方案降低了配煤成本，提高了生产效率，降低了员工的劳动强度，节约了人工成本，显著提高了经济效益。更多还原

【Abstract】 For washing the coal which comes from multiple seams and has varied and changing properties at Luotuoshan Coal Preparation Plant, the problems encountered are complicated coal blending calculations, high labor intensity and low washing efficiency. To tackle these problems, the particles swarm optimization(PSO)—based special mathematic software MATLAB is used to compile and develop the mathematic models. This makes it possible to predict the quantity-quality data and the coal separation parameters based on property of raw coal treated, make optimum calculation of the scheme for washing the different coking coal in blended manner, make rapid and accurate calculation of optimum blending ratios and provide the separation parameters for reference. Study result shows that through adoption of the scheme, while ensuring the quality indices of the clean coal products, there can be seen reductions in coal blending cost, labor intensity and cost, and much improved coal cleaning efficiency and economic result.更多还原