Research and Optimization of Operating Parameters of a Rotor Classifier for Calcined Petroleum Coke

Abstract

This article explores the impact of operating parameters on the classification efficiency of a rotor classifier. Based on the experimental data of calcined petroleum coke classification, a single-factor experimental analysis is conducted to find the relationship between operating parameters and classification performance. The cut size becomes progressively smaller as the rotor speed and feeding speed increase, and progressively larger as the inlet air volume increases. Newton’s classification efficiency and classification accuracy decreased with the increase in feeding speed. The range analysis of the orthogonal experiment shows that the rotor speed and inlet air volume have significant effects on the classification performance, but the effect of feed speed is relatively weak. In addition, the optimal combination of operating parameters is obtained by optimizing the operating parameters. Newton’s classification efficiency under this combination is estimated, and the estimated value is 82%. The verification experiment reveals that the Newton’s classification efficiency is 83.5%, which is close to the estimated value. Meanwhile, the classification accuracy is 0.626. This study provides theoretical guidance for the industrial production of calcined petroleum coke and accumulates basic experimental data for the development of air classifiers.