Modeling and Improving the Efficiency of Crushing Equipment

被引:9
作者
Vasilyeva, Natalia [1 ]
Golyshevskaia, Uliana [1 ]
Sniatkova, Aleksandra [1 ]
机构
[1] St Petersburg Min Univ, Mineral Raw Mat Proc Fac, St Petersburg 199106, Russia
来源
SYMMETRY-BASEL | 2023年 / 15卷 / 07期
关键词
crusher; energy efficiency; modeling; ENERGY-CONSUMPTION; COMMINUTION; WEAR; CRUSHABILITY; VALIDATION;
D O I
10.3390/sym15071343
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Over the last few decades, the demand for energy-efficient mineral-processing methods has continued. The necessity to develop energy-efficient technologies for the mineral industry will increase in the future, considering the exhaustion of high-quality resources and severe environmental limitations. The subject of this study is crushing equipment. It is a complex of units designed to reduce the fraction of ore and non-metallic solid materials. It is also designed to make them more symmetrical in order to facilitate their transport and later use in production. Thus, the urgency of using crushers in mining and processing plants is clear, so it is relevant to find ways to optimize their operation and reduce energy consumption. This article presents a systematic review of the task of improving the energy efficiency of crushing units. This is achieved by studying modelling methods and results, the automation of crushing and grinding processes, and the wear reduction of crusher components. On the grounds of the reviewed sources, the main methods of increasing the efficiency of crushing units are identified. A mathematical model of the cone crusher was designed. The simulation error is less than 6%. A simulation experiment was carried out on the mathematical model. The dependences of the current and power of the crusher electric drive on the feeder capacity are determined; the graphs have a symmetrical position relative to the approximating curve (R-2 & AP; 0.9).
引用
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页数:14
相关论文
共 62 条
[1]   RETRACTED: Machine learning approach to handle data-driven model for simulation and forecasting of the cone crusher output in the stone crushing plant (Retracted article. See vol. 41, 2025) [J].
Abuhasel, Khaled Ali .
COMPUTATIONAL INTELLIGENCE, 2021, 37 (03) :1098-1110
[2]   Optimization and Simulation of Operation Performance in Crushing Plants Using Fuzzy Modelling [J].
Abuhasel, Khaled Ali .
JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING, 2019, 28 (06) :766-780
[3]  
Aleksandrova TN, 2022, J MIN INST, V256, P503
[4]   Different perspectives of dynamics in comminution processes [J].
Asbjornsson, Gauti ;
Tavares, Luis Marcelo ;
Mainza, Aubrey ;
Yahyaei, Mohsen .
MINERALS ENGINEERING, 2022, 176
[5]   Extension, Validation, and Simulation of a Cone Crusher Model [J].
Atta, Khalid Tourkey ;
Euzebio, Thiago ;
Ibarra, Haroldo ;
Moreira, Vinicius Silva ;
Johansson, Andreas .
IFAC PAPERSONLINE, 2019, 52 (14) :1-6
[6]   Modeling and prediction of wear rate of grinding media in mineral processing industry using multiple kernel support vector machine [J].
Azizi, Asghar ;
Rooki, Reza ;
Mollayi, Nader .
SN APPLIED SCIENCES, 2020, 2 (09)
[7]   Benchmarking comminution energy consumption for the processing of copper and gold ores [J].
Ballantyne, G. R. ;
Powell, M. S. .
MINERALS ENGINEERING, 2014, 65 :109-114
[8]   An optimal crusher control: Its design [J].
Bashaleishvili, DI .
AUTOMATION AND REMOTE CONTROL, 2006, 67 (01) :54-64
[9]   Application of multi-disciplinary optimization architectures in mineral processing simulations [J].
Bhadani, Kanishk ;
Asbjornsson, Gauti ;
Hulthen, Erik ;
Evertsson, Magnus .
MINERALS ENGINEERING, 2018, 128 :27-35
[10]   The Present Issues of Control Automation for Levitation Metal Melting [J].
Boikov, Aleksei ;
Payor, Vladimir .
SYMMETRY-BASEL, 2022, 14 (10)