Development of a 3D image analysis method to measure blast-induced fragmentation at the Leveäniemi mine

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Insinööritieteiden korkeakoulu | Master's thesis
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European Mining, Minerals and Environmental Programme (EMMEP)
79 + 22
The first size reduction stage in open pit hard rock mining is blasting and is fundamental for mineral resource extraction as it enables transportation of the rock. Consistent fragmentation results are preferable as it can ease the loading, hauling and crushing stages. Fragmentation analysis assists in identifying areas where similar blast results appear when comparable drill and blast designs are used. Subsequently, drill and blast domains can be defined for the Leveäniemi mine to ease the drill and blast design process. Measuring fragmentation has been continuously researched over the past years. Image analysis methods were developed as it minimised disruption to production and provided a reasonable indirect estimation of particle sizes. So far, research was focussed on 2D image analysis. However, by adding a 3rd dimension, some limitations can be overcome that were experienced when using only two dimensions. Therefore, the potential of 3D image analysis of blasted rock, loaded in haul trucks, is of interest. By evaluating truck loads, the muck pile is better represented in comparison to measuring a whole muck pile. This is one of the few studies done until now on 3D image analysis in open pit mining, analysing material in loaded trucks. A 3D image analysis field test was executed to measure blast-induced fragmentation in a production environment at the Leveäniemi mine. The aim was to gain a clear understanding of the factors contributing to an optimal blast result and to establish blast domains. The test setup consisted of an image acquisition system, photographing truck loads from above using two cameras that were triggered by a laser. RFID truck markers were combined with Minestar data to identify the origin of the truck. Truck loads were analysed using software developed by LKAB and 3GSM, constructing 3D models and automatically delineating particles to analyse fragmentation. No pre- or post-processing of the images or delineation results have been done. Drill and blast, and muck pile shape parameters were acquired as well. The results show x50 particle sizes ranging from 5 to 56cm and x80 ranging from 20 to 150cm. Care should be taken when interpreting these results due to the limited amount of data analysed and bias in the measurements and software. Fines are underestimated and correct particle delineation occurred on average in 42% of each load. The limited amount of data resulted from the practical problems arising during data acquisition. Continuous data acquisition of images was not achieved. Correlation of fragmentation to drill and blast, or muck pile shape parameters was not achieved due to the challenges faced. 3D image analysis of truck loads proved to have potential but requires many modifications and developments to the system and software to achieve continuous data acquisition. A focus on image quality and the practicalities of the system is recommended. Continuous data acquisition is required when using fragmentation analysis for establishing blast domains. Comparable and repetitive measurements are the main prerequisites for choosing a method to analyse fragmentation for the purpose of defining blast domains. Hence, other methods like using drones to analyse whole muck piles after blasting should be considered, though it would statistically be less representative. For the Leveäniemi mine, it is recommended to achieve geotechnical domains including joint spacing and orientation before a follow-up study is started on blast domains. Additionally, the development of this method should be finalised, or an alternative is recommended.
Leveinen, Jussi
Thesis advisor
Sormunen, Matti
3D image analysis, fragmentation, blasting, open pit mining, explosives
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