Research On The Main Process Parameters Of Heavy Medium Separation Based On SPSS Software

Heavy medium cyclone separation is the most commonly used method in coalpreparation plant. But because there are many factors which can influence thecyclone separating, the cyclone separation efficiency has not reached the highest inthe actual production process. This thesis is mainly focused on the SPSS statisticalanalysis of process parameters which affecting the heavy medium cyclone separationanalyzed according to the real-time data collected in Xingtai Coal Preparation Plant.The main process parameters affecting the heavy medium cyclone separationare: raw coal ash content, heavy medium density, magnetic material content, themedium inlet pressure, the feeding quantity, etc. In this paper, taking heavy mediumcyclone separation system in Xingtai Mine Coal Preparation Plant as the researchobject, through the sampling of cyclone feed and products, floating and sinking test,to calculate the yield with Geshi method, draw the distribution curve, check theactual separation density. At the same time, recording the real-time data of everyprocess parameter at sampling points. Through the obtained data, first regressionanalysis with the separation density as the dependent variable, raw coal ash content,medium density, magnetic material content, medium inlet pressure, feeding quantityas independent variable to establish the model equation; then set up the relationshipmodel between two sections of actual separation density to implement the forecastingof the second separation density through the first separation density. The most directindex to evaluate heavy medium cyclone separating effect is product structure, sothis paper through the analysis of multiple data, established the relationship betweenthe clean/middle coal structure, separation density and the process parameters, inorder to achieve the timely adjustment to achieve the best separation conditionsaccording to the product structure.In this paper, the model was tested on the month comprehensive data in XingtaiCoal Preparation Plant, the actual production situation shows that the model canbetter reflect the actual production to some extent, but there is a certain deviation, soit also needs to be improved.