Multi-Objective Optimization of Impact Crusher Rotor Based on Response Surface Methodology

Li-Mei Zhao*, Lun-Jun Chen, Feng He, Yu Luo
College of Mechanical Engineering, Guizhou University, Gui yang, 550025, China

© 2014 Zhao et al

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: ( This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the College of Mechanical Engineering, Guizhou University, Gui yang, 550025, China; Tel: 0851-5281078; E-mail:


In this study, a method of multi-objective optimization is proposed to improve the quality of crushed materials and vibration performance of the rotor. This method is driven by the first order natural frequency and the radius of the rotor. The Central Composite Design (CCD) experiment method was used to guide the selection of appropriate structure finite element analysis samples in design space. The quadratic polynomials were employed to construct response surface (RS) model based on the response outputs of these samples obtained by analyzing the first order natural frequency, the harmonic and mass with the software ANSYS. Well-distributed samples were generated in the design space by shifted Hamersley sampling method. The prominent points were selected by the weighing method as initial samples. The multiobjective genetic algorithm was used to obtain the Pareto optimal solution set. Through optimization, the first order natural frequency was increased by 5.5%; the radius of the rotor was enlarged by 2.5% and the amplitude of the vibration was decreased by 11% at the position of bearing. At the same time, the rotor mass did not change much. The results show strong engineering practicability of the proposed method.

Keywords: Finite-element analysis, multi-objective optimization, optimization design, response surface methodology.