Structural optimization of mining decanter centrifuge based on response surface method and multi-objective genetic algorithm

Abstract

A significant quantity of slime water generated during coal mining poses a serious threat to the health of underground workers and the environment. The decanter centrifuge is widely employed in slime water treatment due to its high efficiency in solid-liquid separation. This paper proposes a structural optimization framework for the mine decanter centrifuge based on the Response Surface Method (RSM) and Multi-Objective Genetic Algorithm (MOGA). Firstly, a three-dimensional numerical model of the decanter centrifuge was established, and the reliability of the model was verified by experimental and theoretical analysis. Subsequently, the Box-Behnken design method and RSM were employed to construct a response surface model that links input parameters (drum half cone angle, screw pitch, and spiral blade Inclination angle) with target variables (solid phase recovery rate and overflow liquid phase solids content). The interactions between each input parameter and target variable were assessed using analysis of variance (ANOVA), which confirmed the model's effectiveness and generalization capability. Finally, MOGA was employed to optimize the centrifuge's structural parameters, resulting in an 8.16 % increase in solid recovery rate and a 35.84 % reduction in overflow liquid solid content. It offers a valuable reference for the structural optimization of decanter centrifuges in coal slurry separation.