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Tongqing Li [1; 2; 3] and Yuxing Peng [1; 2; 3] and Zhencai Zhu [1; 2; 3] and Zhangfa Yu [4] and Zixin Yin [1; 2; 3]

Academic Editor: Alain Portavoce

1, School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, China, cumt.edu.cn

2, Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment, China University of Mining and Technology, Xuzhou 221116, China, cumt.edu.cn

3, Jiangsu Collaborative Innovation Center of Intelligent Mining Equipment, Xuzhou, China

4, State Key Laboratory of Mining Heavy Equipment, CITIC Heavy Industries Co., Ltd., Luoyang 471000, China

Received May 25, 2017; Revised Sep 6, 2017; Accepted Sep 28, 2017

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

Size reduction of minerals by grinding hitherto is a significant step in whole stage of mineral processing in which feeds are reduced in size to liberate impurities and to change the particle size distribution. The operating costs associated with size reduction are a significant discipline in mineral industry [1, 2]. Grinding is known to be an energy-intensive operation process, since it consumes approximately two-thirds of the total energy of the mineral processing plants [3]. The literature reported that the power estimation of tumbling mills plays an important role in determining the grinding efficiency and mill performance [4, 5]. To this end, establishing power equations of tumbling mill has attracted much attention in recent years. At present, researchers presented that mill power strongly affected by the flow properties of materials in mills [6–8]. Besides, with the rapid development of computing power and advanced contact algorithm, the Discrete Element Method (DEM) has been extensively used as a leading tool in tumbling mills. DEM simulations hitherto have been demonstrated extremely desirable to predict what happens in reality as well as the quantitatively accurate information representation inside mills, while the accuracy of outcomes for DEM simulations highly depends on the input parameters [9–14]. So far, the sand-pile calibration has been employed exclusively in determining the input parameters. The aim of this approach was to make an approximate comparison between angle of repose of experimental results and the one obtained by DEM numerical...

  

  

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