A real-time analysis of post-blast rock fragmentation using UAV technology

Abstract

Accurate measurement of blast-induced rock fragmentation is of great importance for many mining operations. The post-blast rock size distribution can significantly influence the efficiency of all the downstream mining and comminution processes. Image analysis methods are one of the most common methods used to measure rock fragment size distribution in mines regardless of criticism for lack of accuracy to measure fine particles and other perceived deficiencies. The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using Unmanned Aerial Vehicles (UAVs) for collecting images of rock fragments can not only improve the quality of the image data but also automate the data collection process. Ultimately, real-time acquisition of high temporal-and spatial-resolution data based on UAV technology will provide a broad range of opportunities for both improving blast design without interrupting the production process and reducing the cost of the human operator. This paper presents the results of a series of laboratory-scale rock fragment measurements using a quadrotor UAV equipped with a camera. The goal of this work is to highlight the benefits of aerial fragmentation analysis in terms of both prediction accuracy and time effort. A pile of rock fragments with different fragment sizes was placed in a lab that is equipped with a motion capture camera system (i.e., a high-accuracy indoor GPS-like system) for precise UAV localization and control. Such an environment presents optimal conditions for UAV flight and thus, is well-suited for conducting proof-ofconcept experiments before testing them in large-scale field experiments. The pile was photographed by a camera attached to the UAV, and the particle size distribution curves were generated in almost real-time. The pile was also manually photographed and the results of the manual method were compared to the UAV method.

The Fragmentation Energy-Fan Model in Quarry Blasts

“…The size distribution of blasting products can only be measured accurately enough by sieving the muckpile, a complicated, costly and disruptive to production task. Although enhanced 2D technologies (often called 3D though they are not really determining fragmentation of a rock volume) to monitor fragmentation are available, such as LiDAR imaging-laser imaging detection and ranging (McKinnon and Marshall 2014;Oñederra et al 2015;Thurley 2013;Thurley et al 2015) or photogrammetry (Noy 2013(Noy , 2015Bamford et al 2016), 2D image analysis is still the most common tool used. Image analysis systems may show a poor performance at small sizes especially when they have not been calibrated (Sanchidrián et al 2009) and it is advisable to use additional tools to correct raw data on a blast per blast basis in order to get a good estimation of the actual size distribution (Sanchidrián et al 2006).…”

Breaking new ground: challenges and opportunities for maximising value from underground blasting

“…This approach has been significantly developed and is widely used for rock mass characterisation in civil and mining engineering projects (Fekete & Diederichs 2013;Riquelme et al 2014). Bamford et al (2016) also tested the application of unmanned aerial vehicle (UAV) technology for the collection of images from the muck piles to overcome the errors that can be introduced by human applications. These days, drones are widely used for the analysis of rock fragmentation, especially in surface mining.…”

Towards Automatic Classification of Fragmented Rock Piles via Proprioceptive Sensing and Wavelet Analysis

“…Capturing images or scans also requires close proximity to rock pile, which leads to disruption to the mining process and results in in-frequent data capture. Research into using drones outfitted with scanners has attempted to remove the intrusiveness of data capture [6].…”

“…This size reduction is an energy intensive process that consumes a significant portion of a mine's operating cost [3], [4] and 3% of global electric power generated [5]. Research focusing on the dynamic optimization of the comminution circuit highlights that large variations in the feed size of rocks can lead to suboptimal operations and increased maintenance costs [6]. Accurate and frequent information is needed to ensure design specifications are met and equipment is operating at optimal levels.…”

“…Accurate and frequent information is needed to ensure design specifications are met and equipment is operating at optimal levels. Current rock size (fragmentation) estimation technologies use exteroceptive sensors (e.g., cameras, LiDAR) [6], [7]. Drawbacks to these sensors are that they are only able to see the surface of a rock pile, cameras require specific lighting conditions and positioning, and significant time to safely acquire the data.…”