MatrixGroup

Adelaide, Australia

MatrixGroup

Adelaide, Australia
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Zhao S.,University of Adelaide | Lu T.-F.,University of Adelaide | Koch B.,MatrixGroup | Hurdsman A.,MatrixGroup
International Journal of Mineral Processing | Year: 2013

Geometric stockpile models are always used to estimate the quantity and quality of iron ore in stockpile management systems. However, most of these models are not suitable for quality control purposes in iron-ore export facilities because no measurement device is used to continuously provide updated information for the modelling. This paper presents a solution to accurately measure profiles along the stockpile surface in real time and automatically models the 3D stockpile during stacking and reclaiming operations. Using a 2D laser range finder, the spatial data of a stockpile, such as the positions of different layers, the cutting surfaces during the reclaiming are represented by mathematical equations. Experiments conducted in a laboratory environment indicated good results and proved that the modelling approach is accurate and efficient. By making available the latest shapes of stockpiles and quality information, it is possible to predict the tonnage and quality grade with a greater degree of accuracy. Also, together with the reclaimer position data, it is possible to develop adaptive reclaiming algorithms to continually adjust the quality with respect to the quality requirement, which warrants meeting the required quantity and quality while enhancing the export efficiency and increasing productivity. © 2013 Elsevier B.V. All rights reserved.


Zhao S.,University of Adelaide | Lu T.-F.,University of Adelaide | Koch B.,MatrixGroup | Hurdsman A.,MatrixGroup
IEEE International Conference on Automation Science and Engineering | Year: 2012

Bucket Wheel Reclaimers (BWRs) normally travel on a rail among stockpiles to perform stacking and reclaiming operations. Currently, the position accuracy of the bucket wheel at the end of boom measured by the onboard encoder system is limited to 30cm. To maintain such accuracy, calibrated points have to be placed along the rail, which is inefficient and costly. This paper proposes a simulation study using Unscented Kalman Filter (UKF) algorithm to fuse DGPS and encoder data for BWR localization. The results obtained indicate that the errors in positional accuracy are better than 15cm and UKF is an objective technology that can be applied to localize such large scaled machine. © 2012 IEEE.


Zhao S.,University of Adelaide | Lu T.-F.,University of Adelaide | Koch B.,MatrixGroup | Hurdsman A.,MatrixGroup
International Journal of Mineral Processing | Year: 2015

This paper describes an innovative method to calculate the quality of a stockpile in real-time to improve the efficiency in stockpile blending operations. A stockpile is modelled as a grid of voxels (octants), which are used as geometric elements for both quality calculations and result storage. The quality calculation is based on the real geometric shape of the stockpile which is measured by a laser scanner. Furthermore, a BWR (Bucket Wheel Reclaimer), which is treated as a mobile robot arm, is incorporated into this model to predicate the quality of the reclaimed material. Thus, this 3D quality embedded model can be used to calculate, plan, control and predict the quality level of iron ore being stacked and/or reclaimed with a great degree of accuracy. This model provides an opportunity to monitor and track quality data throughout the blending operations. It will lead to proactive and continuous blending activities that fundamentally improve quality control and increase efficiency in stockpile management. © 2015 Elsevier B.V. All rights reserved.


Zhao S.,University of Adelaide | Lu T.-F.,University of Adelaide | Koch B.,MatrixGroup | Hurdsman A.,MatrixGroup
2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012 | Year: 2012

The delivery of a relatively constant quality grade of iron ore is crucial to Australia mining. As a buffer, blending and target grading system, stockpile plays a key role in the iron ore quality control. However, the shape of the stockpile, the quantity housed within the stockpile and the quality grade inside the stockpile are currently unavailable to operators. Therefore, this paper describes a method to generate 3D model of a stockpile with multiple layers using laser to keep tracking the shape changes caused by the stacking and reclaiming operations. Using this 3D model, the volume can be easily calculated anytime. Experiments conducted in laboratory environment indicate good results and proved that the 3D modelling method is accurate and efficient. © 2012 IEEE.

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