Optimization of Process Parameters of Air Classifier Based on Particle Trajectory

Under the rapid development of the world’s powder technology, powder materials are used in a wide range of fields such as metallurgy, chemical industry and petroleum. Turbo air classifier is one of the most important mechanical equipment in the industrial field in term of powder process equipment. To study the production efficiency of ultrafine powder, the gas-solid two-phase flow in the kff-400 air classifier was numerically simulated using Fluent software. The RNG <i>k</i>-ε turbulence model and the random particle orbit model were selected. The influence of the rotor RPM and the air intake on the particle trajectory in the flow field of the kff-400 air classifier was analyzed. Based on the numerical simulation result, taking several sets of rotor RPM and air intake with good performance as process operation parameters and the product size distribution as the inspection index, the powder classification test was carried out. The test data show that the kff-400 turbo air classifier, producing a particle size of 1 200 mesh barite and iron ore powder with the highest relative precision, has the process parameters of 2 200 r/min and the inlet velocity of 8 m/s. The research results could provide theoretical basis and engineering application reference for ultra-fine iron ore powder and barite production.