Simulation and optimization of crushing chamber of gyratory crusher based on the DEM and GA
| Autor: | Guoqiang Wang, Da Cui, Zeren Chen, Duomei Xue |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Materials science
business.industry General Chemical Engineering 02 engineering and technology Structural engineering Radius 021001 nanoscience & nanotechnology Discrete element method Crusher 020401 chemical engineering Genetic algorithm Particle Granularity 0204 chemical engineering 0210 nano-technology business Nonlinear regression Power density |
| Zdroj: | Powder Technology. 384:36-50 |
| ISSN: | 0032-5910 |
| DOI: | 10.1016/j.powtec.2021.02.003 |
| Popis: | To optimize the crushing chamber of the gyratory crusher, the discrete element method (DEM) is used to explore the influence of the concave curve height, concave curve radius, eccentric angle, and mantle shaft speed on the performance of the crushing chamber in this paper, here, the DEM analysis model of iron ore particle is established based on the bonded particle model. Based on this, a prediction model of the crushing chamber performance is established through the multiple nonlinear regression, and the multi-objective optimization is performed based on the genetic algorithm (GA). The corresponding optimization values are 450 mm, 950 mm, 0.2°, and 100 rpm, respectively. Finally, the validity of the optimization results is verified by DEM simulation, and the results show that productivity and power density is increased by 36% and 26%, respectively. The optimized crushing force is approximately twice the one before optimization. Both discharge granularity and power consumption are reduced to varying degrees. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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