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Blast fragmentation measurement based on 3D imaging in sublevel caving draw-points and LHD buckets at LKAB Kiruna
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Innovative Machine Vision.ORCID iD: 0000-0001-6186-7116
Mining Technology R and D, LKAB Kiruna Mine.
Mining Technology R and D, LKAB Kiruna Mine.
2015 (English)In: Proceedings of the 11th International Symposium on Rock Fragmentation by Blasting: Fragblast 11, Carlton, VIC: The Australasian Institute of Mining and Metallurgy, 2015, 763-774 p.Conference paper, Published paper (Refereed)
Abstract [en]

To assess the present-day functionality of large-scale sublevel caving (SLC) at LKAB Kiruna a comprehensive measurement program was undertaken involving blast function, fragmentation and gravity flow. As part of this assessment, a fragmentation measurement trial was performed based on 3D imaging ofthe draw-point and corresponding bucket load of the underground load-haul-dump (LHD) excavator. 3D image data from stereo photogrammetry was collected and an automated image analysis strategy developed. A number of data sets were collected for each of the draw-point and LHD bucket, along withsieving results for four of the LHD bucket loads (totally about 70 tonnes). Two of the sieving results were used to inform the automated image analysis strategy, and two were held back as a comparison. Large variations in the visible particles are apparent when comparing corresponding draw-points and LHD bucketshighlighting the impact of sampling location and the need to measure large quantities of data in order to avoid bias from small samples. The results show that 3D imaging and analysis can produce fully automated measurement and analysis of the visible particle size distribution. Although this is not the same as the sievesize distribution it provides useful estimation of both the larger size classes and a bulk estimate of fine material below approximately 60mm. The 3D stereo photogrammetry measurement system used produced very high 3D point density but this was achieved using a custom up-sampling technique which significantly smoothed the data, removing small particles, smoothing edges, and this negatively affected the particle delineation algorithms.

Place, publisher, year, edition, pages
Carlton, VIC: The Australasian Institute of Mining and Metallurgy, 2015. 763-774 p.
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-31127Local ID: 5332858d-378c-4cbf-8a4e-49d3736d0348ISBN: 9781925100327 (print)OAI: oai:DiVA.org:ltu-31127DiVA: diva2:1004357
Conference
International Symposium on Rock Fragmentation by Blasting : 24/08/2015 - 25/08/2015
Note
Godkänd; 2015; 20150318 (mjt)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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Other links

http://www.innovativemachinevision.com/fragmentation-assessment-studies-for-mining/Denna studie bedömning fragmentering genomfördes i samarbete med Innovativ Machine Vision. Kvantitativt jämföra fragmentering i sprängning och grottforskning med fragmentering mätning för underjords "drawpoints" och dagbrott "muckpiles"

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Thurley, Matthew

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CiteExportLink to record
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