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本文阐述了动力用煤按粒度分级对节约煤炭能源和合理加工利用煤炭资源的重要意义。但是,当前对外在水分在7％以上的煤炭进行细粒级筛分尚无有效方法。本文作者利用概率论的原理研究了粒状物料的透筛速度和筛分动力学以及相对粒度、筛面倾角、颗粒投射方位角等因素与粒状物料透筛概率之间的相关关系。 实验室试验研究表明:采用大倾角、大筛孔的筛面可以有效地从外在水分为7～12％,粒级为13mm～0的原煤中分离出6mm～0的粉煤。GS—1000×2000型概率分级筛的工业性试验表明:能有效地处理原煤粒度为50mm～0、外在水分为7～14％的煤炭的分级,筛分成+25,13～25,6～13和—6mm的粒级煤产品,处理量达70～80T/H。
This paper expounds the importance of dynamic coal classification according to grain size to save coal energy and rationally process and utilize coal resources. However, at present, there is no effective way to conduct fine-grading screening of coal with external moisture above 7%. The author uses the principle of probability theory to study the relationship between the penetration speed and sieving kinetics of granular materials, the relative particle size, the inclination angle of the sieve surface, the azimuth angle of grain projection and the probability of granular material sieving. Laboratory tests show that the use of large-angle, large screen mesh sieve surface can effectively from the external moisture is 7 ~ 12%, the particle size of 13mm ~ 0 6mm ~ 0 raw coal was separated 6mm ~. The industrial test of GS-1000 × 2000 probabilistic grading sieve shows that it can effectively classify the coal whose raw coal particle size is 50mm ~ 0 and external water is 7 ~ 14%, sieve it into +25, 13 ~ 25, 13 and -6mm grain coal products, processing capacity of 70 ~ 80T / H.