Copper Ore Quality Tracking in a Belt Conveyor System Using Simulation Tools

Abstract

The ore quality at mining faces in the KGHM underground copper ore mines can be determined based on channel samples and block models built in the Datamine system. Unfortunately, even very accurate information regarding the quality of deposits at mining faces does not translate into the possibility of predicting the composition of feed to enrichment plants. The mixed ore from mining faces is cyclically loaded by trucks onto belt conveyors, which in turn convey it to shafts. When transported on the conveyors, mixed ore portions from many loading points form a divisional stream, which then goes to the main haulage conveyors where ore streams from various divisions are combined. The way of filling the bunkers, as well as ore flow temporary stoppages, changes the sequence of ore mixing and its arrival, which hinders the ability to track its quality. In the current study, radiofrequency identification (RFID) was proposed for tracking ore composition. A complementary method of ore quality prediction comes from simulating the tagged ore flow within the FlexSim software package. The discrete element method (DEM) of simulations, verified by experiments with RFID tags, can determine the ore flow through bunkers. Forecasts of ore feed composition for the next shift can be prepared with actual plans of mining division operations, the filling level of bunkers and the work plan of the transport system.

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training

“…The RFID system is primarily composed of two technological parts: electronic tags and readers. Other parts, such as computers, networks, and wireless devices, can be added based on these two components to work together and constitute a complete solution [ 13 ]. Electronic tags are tools to store attribute information of objects, which are generally placed on the surface or inside of objects and composed of antennas and electronic chips [ 14 ].…”

Improvement of methods for description of a three-bunker collection conveyor

“…The issue of modeling the transport system for the general case, assuming the presence of variable transport delays, remained unresolved. The use of the discrete element method [18], a neural network [19,20], and specialized software [21] in modeling a three-bunker collection conveyor can be considered as suggested ways to overcome these difficulties. However, the proposed solutions to the problem require significant computing resources, which limits their practical use for the synthesis of control systems.…”

“…However, the proposed solutions to the problem require significant computing resources, which limits their practical use for the synthesis of control systems. This explains the lack of publications containing methods [18][19][20][21] for constructing models for a collection conveyor scheme with three accumulating bunkers. Another approach to solving the problem is to develop analytical models of a multi-section transport conveyor.…”

“…Taking into account these assumptions, the equation determining the state of the flow parameters of the m-th linear conveyor takes the form [17,18]:…”

In-truck ore grade estimation using apparent density measurements

“…Published accounts of prompt measurement or estimation of ore grade very early in the mining process are scarce. An approach using RFID tags to trace ore movement on conveyors in underground mines was attempted at Vale Inco (Fiscor, 2007) and at KGHM (Bardzinski et al, 2020). This approach, however, relies on modelling qualitative data (ore source and type, RFID timestamps, etc.)…”