Parameter optimization of an industrial water injection hydrocyclone in the Taixi coal preparation plant

An industrial water injection hydrocyclone was adopted in the Taixi coal preparation plant to overcome the shortcoming of fine particle entrainment in the underflow and improve the grading efficiency. Parameter optimization of the hydrocyclone was critical prior to putting it into production. A particle swarm optimization optimized support vector machine (PSO-SVM) model based on uniformly designed experiments was built. It was satisfactory in accuracy as the average of the absolute of relative error was 1.73% for the training dataset, and the relative error of the test dataset was 8.43%. The trends of grading efficiency versus underflow port diameter, inlet pressure and water injection pressure were analyzed, respectively. It was found that the maximum efficiency was obtained when underflow port diameter was 50 mm, inlet pressure was 0.25MPa and water injection pressure was 0.04 MPa.

Automated summary

An industrial water injection hydrocyclone was adopted in the Taixi coal preparation plant to overcome the problem of fine particle entrainment and improve grading efficiency. The parameter optimization of the hydrocyclone was conducted using a particle swarm optimization optimized support vector machine model. The study found that the maximum efficiency was achieved with a 50 mm underflow port diameter, 0.25 MPa inlet pressure, and 0.04 MPa water injection pressure.