Study On The Process Parameters Of Coarse Slime Recover System In Luling Coal Preparation Plant

As an important part of the clean coal technology, coal processing technology has been continuously developmented in our country. Currently, China’s coal preparation plant mostly used dense medium for coarse coal separation and the flotation for slime. However, due to the granularity floor level of the dense medium cyclone is rising and the upper limit of flotation is declining.The coarse slime between the effective separation limit of dense medium cyclone and the effective separation limit of flotation has not been separated effectively. With the continuous improvement of mechanize coal mining, the content of pulverized coal in raw coal has increased and the coarse slime also increased. If the coarse slime of this part don’t been properly recycled, it will seriously affect the normal production of the coal preparation plant. In recent years, the coarse slime separation has been more and more attentied. Serve the problem of coarse slime separation can reduce the contamination of commercial coal,and ensure the quality and yield of commercial coal.It can also reduce the production costs and improve economic efficiency of coal preparation plant.Currently, China’s coal preparation plant commonly used the process equipment such as heavy medium cyclone, spiral separator,teetered bed separator, water medium cyclone, curved screen and slime centrifuge for coarse slime recovery. These process equipment have their own advantages and disadvantagesand and it can also affect the recovery efficiency if the process parameters has changed.This study test studed the coarse slime recovery system in Lulling Coal Preparation Plant. Compared the different process parameters and screening effect of curved screen by replacing the sieve. Compared the difference of coarse slime recovery system before and after replaced the sieve through analysised the feeding and product of curved screen and slime centrifuge. In the process of data analysis,used data fitting, mathematical model and solver method to determe the parameters for evaluating the screening performance.