Measuring blast fragmentation at Esperanza mine using high-resolution 3D laser scanning

Abstract

Image analysis as a technique for fragmentation measurement of rock piles has been the subject of research since the 1980s, and to date, run of mine (ROM) fragmentation optimisation studies have primarily relied on particle size measurement using photographic-based 2D imaging systems. Disadvantages of 2D imaging systems include particle delineation errors because of variable lighting and material colour and texture variation; no direct measure of scale and perspective distortion; and inability to distinguish overlapped particles, non-overlapped particles, and areas of fines. With the development of 3D imaging technologies, there is an opportunity to develop techniques that could improve data collection and overcome the limitations of existing 2D image-based systems. This paper describes the first attempt to use 3D high-resolution laser scanning techniques to quantify 'whole of muckpile' fragmentation from full-scale production blasting. During two monitoring campaigns in 2013, high-resolution laser scanning data were collected from production blasts at Esperanza mine (Antofagasta Minerals Group). Fully automated analysis of the 3D data was possible in all cases where the data were of sufficiently high resolution. Manual pre-processing was required when the data were of low resolution to specify the region of fines. Overall results indicated that ROM fragmentation requirements were meeting specified targets, despite the marked differences in powder factors. This was particularly the case for those blasts conducted in similar geological domains. This work has demonstrated that high-resolution laser scanning can be used as an alternative technique to measure 'whole of muckpile' fragmentation in production blasting.

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).…”

3-D Granulometry Using Image Processing

“…Table I presents the list of notations and parameters used in the paper. II. PREVIOUS WORK Currently, the vast majority of granulometry methods based on image processing techniques perform a two-dimensional (2D) analysis, and only a few works perform 3D measurements [12].…”

“…Approaches that only analyze 2D images have important disadvantages with respect to methods analyzing 3D models since they can have difficulties dealing with illumination changes or with variations in the intensity and texture of the materials [12]. Considering the approaches based on 2D images, the additional information in color images with respect to grayscale images can help in achieving a more robust segmentation of the particles by considering the color difference between the texture of the material and the background.…”

“…3D scanners [22] have demonstrated their robustness in measurement applications [12]. Nevertheless, this kind of solution requires the use of complex and expensive hardware.…”

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

“…Using 3D measurements for rock fragmentation analysis eliminates the need for scale objects and reduces the error produced by the shape of the muck pile. If measurements are taken with a LIDAR station, then the error produced by uneven and suboptimal lighting conditions can be eliminated [5] as well. While these techniques reduce the limitations imposed by 2D photos, there are still aspects that can be improved.…”