摘要:
本开滦地区的炼焦煤泥属于典型的难浮煤泥,长期以来,煤泥的浮选精煤可燃体回收率较低,浮选尾煤灰分也偏低,导致大量高品质稀缺资源的流失.本文通过对该难选煤泥进行一定的物性分析,采用磨矿手段进行矿物解离,探究磨矿工艺对煤泥浮选效果的影响,寻求释放稀缺资源、提高浮选精煤回收率的新途径.通过红外、衍射、扫描电镜等一系列现代分析测试手段分析发现:该浮选煤泥变质程度不深,煤中主要赋存有高岭石和石英等矿物杂质;颗粒呈碎散状分布,表面及裂隙中赋存有大量微细粘土类矿物质,其较高的比表面能易与煤形成竞争性吸附,导致煤泥难选.结合小筛分、小浮沉等基础试验分析发现:该煤泥中间密度级含量较高,煤与矿物杂质多以连生体形式出现;当预制精煤灰分为12%时,该煤泥属中等可浮.通过对浮选的中煤进行磨矿再浮选,其精煤可燃体回收率达到77.85%,灰分为12.50%.较原煤磨矿浮选的回收率提高了5.13%,较原煤直接浮选的回收率提高了8.23%,对提高资源利用率的效果显著.
Abstract:
Kailuan coking coal mud area is a typically difficult floated slime.Over years,the recovery of combustible ash flotation is slightly loco and so is the ash content in tailing coal flotation,which results in high quality scarce resources run off.In this paper,through the physical property analysis of the selected slime,the mineral liberation method is used to explore the effect of the grinding process on the flotation of coal slime.Seek new ways of releasing scare resources and improving the recovery of coal flotation concentrate.By a series of modern analytical methods,such as IR,diffraction and scanning clestron microsopy,the study gets some discoveries as follows:the metamorphism of the flotation slurry is not deep and the main content in coal are mineral jmpurities like kadinite and quartz;coal particles take on a scattering distribution and there are a great deal of fine clay minerals on particles'surface and fractures,among which higher surface is liable to competitive adsorption with coal,which can lead to refractory slurry.Combining those basic tests like screening and drifting and so on,the study gets that:the density of the middle part is higher;Coal and mineral impurities are usually in the form of intergrowth.When prefabricated fine ash gets to 12%,the coal slurry is categotized into medium floating.Test results show that the combustible recovery rate of middings coal grinding flotation was 77.85%,ash 12.50%.Compared with the raw coal grinding flotation,the recovery rate was increased by 5.13%,Compared with the direct flotation of raw coal,the recovery rate was increased by 8.23%,which is efficient to improve the resource utilization.