Particle Per-dispersion And Application Of A Superfine Classifier

Particle per-dispersion is an important factor affecting the classificationperformance. Non-uniformity was used to describe the uniformity of particleconcentration distribution, and then to reflect the particle dispersion effect. Thecomputational fluid dynamics (CFD) technology was applied to analysis theeffect of feeding pipe, upper and under feeding types on the particleconcentration distribution uniformity with defferent structural parameters,operating parameters and material parameters. The application of superfineclassifier was studied by experiments with the material of fly ash and bauxite.After the calculation model was verified, the gas-solid flow field of thefeeding pipe was simulated. The effect of guide vanes number, size, spacingassignment, gas velocity, feeding concentration, particle diameter, graduation,density on the particle concentration distribution uniformity was comparativelyanalyzed. The results show that the guide vanes can improve the particledispersion performance. The uniformity of particle dispersion becomes betterwith the increase of the gas velocity, and becomes worse with the increase of thefeeding concentration and particle diameter.The flow field of classifier with upper and under feeding type was simulatedwith Euler-Lagrange method. The pressure difference, the uniformity of airvelocity and particle concentration distribution was analyzed with differentoperating parameters and material parameters. Compared with the under feedingtype, the pressure drop between inlet and outlet of the classifier with upperfeeding type is bigger for adding the mechanical spreading plate. The tangentialand radial velocity of cylindrical surface along the rotor distributes more uniform,and this can help to obtain fine powder with narrow particle size distribution.Particles of cylindrical surface along the rotor distribute more uniform aftermechanical dispersion by the spreading plate. Good particle dispersion is helpfulto classification.The application of superfine classifier with upper and under feeding typeswas studied by experiments. Effect of different operating parameters andmaterial parameters on the particle concentration distribution uniformity was studied, and the feature particle size and size distribution of fine power werecomparatively analyzed. The results show that, both under and upper feedingtype can obtain good classification performance. After classification, the size offine powder is small and of narrow distribution, mainly in1~30μm. Thepercentage of particle less than30μm of fine powder is above90%. The studyresults have guidance to optimize the feeding type, improve the particledispersion of a superfine classifier, and design the operating parameters ofclassification system.