Abstract: This paper mainly studied the fine coal classification efficiency with self-developed deep cone interference settling classifier under different influencing factors.The results show that the water supply using the bottom and the central form at the same time，is conducive to fine coal classification，and the bottom water volume to the central water volume (the ratio of flow) has impact on the classification efficiency，but not obvious.Also the feeding velocity and density is lower，fine coal classification efficiency is higher.Optimization the suitable conditions as follows：the flow ratio is 2∶1，feeding speed is 0.50 m/s，pulp density is 40%，particle size slopes (0.25-0.125 mm and 1.0-0.25 mm) classification efficiency is close to 65%.Compared with the conventional cyclone，the classification efficiency is increased by about 5%-15%.The experimental results show that deep cone interference settling classifier can effectively realize the fine coal classification.