Technical Note Correction of image processing method for determining the size distribution of fragmentation from the blasting at the Choghart mine

Document Type : Original Article

Authors

1 Associate Professor, School of Mining, College of Engineering, University of Tehran.

2 PhD Candidiate, Department of Mining, Faculty of Engineering, University of Kashan,

3 MSc Student, Department of Mining, Faculty of Engineering, University of Kashan,

Abstract

Assessment and prediction of rock fragmentation by drilling and blasting operations, the most basic and most critical parameters affecting the economy of mine is considered. Choghart mine had one of the largest Iran iron ore mine that annual eight million tons of iron ore is extracted from it. In the mine mining operations, including drilling, blasting, loading, transportation and processing is done on a daily basis. Distribution of aggregation from blasting operations and resulting machinery production, mining costs may be reduced. There are several methods to determine the blasting fragmentation and currently, the use of image processing systems is appropriate and effective method for evaluating of blasting fragmentation. In this study, sieve analyzes of three patterns of explosive in Choghart mine and fragmentation curve obtained by the image processing method is compared and then this method for more accurate predictions in mine by factors of α and β is correct. The correction factors value respectively is 0.81108 and 0.82087.

Keywords

References

Akbari, M., Lashkaripour, G.R.,  Bafghi, A.Y. 2014. assessment and classification of rock mass properties in iron central ore mines: J. Appl. Environ. Biol. Sci 4. 10: 140-148.
Akbari, M., Lashkaripour, G., Yarahamdi Bafghi, A. ,Ghafoori, M., 2015. Blastability evaluation for rock mass fragmentation in Iran central iron ore mines: International Journal of Mining Science and Technology.
Carlsson, O., Nyberg, L., 1983. A Method for Estimation of Fragment Size Distribution with Automatic Image Processing, In: Proceedings of the the 1st International Symposium on Rock Fragmentation by Blasting, Holmberg, R., Rustan, A., Lulea University of technology, Lulea, Sweden, p.p. 333-345.
Elgin, I. C., 2010. A practical method of bench blasting design for desired fragmentation based on digital image processing technique and Kuz-Ram model: International Journal on Rock Fragmentation by Blasting-FRAGBLAST9, p.p. 257-263.
Faramarzi, F., H. Mansouri,  MA Ebrahimi Farsangi., 2013.  A rock engineering systems based model to predict rock fragmentation by blasting:  International Journal of Rock Mechanics and Mining Sciences 60, p.p. 82-94.
Latham, J.P., Kemeny, J., Maerz, N., Noy, M., Schlifer, J., Tose, S., 2003. Ablind Comparison Between Results of Foure Image Analysis Systems Using a Photo-Library of Piles of Sieved Fragments: International Journal on Rock Fragmentation by Blasting-FRAGBLAST, Vol. 7, No. 2, p.p. 105-132.
Liu, Y., Nadolski, S., Elmo, D., Klein, B.,  Scoble, M., 2015. use of digital imaging processing techniques to characterize block caving secondary fragmentation and implications for proposed cave-to-mill approach: 49th U.S. Rock Mechanics/Geomechanics Symposium, San Francisco, California.
Raina, A. K., et al., 2010. Productivity improvement in an opencast coal mine in India using digital image analysis technique: International Journal on Rock Fragmentation by Blasting-FRAGBLAST 9, p.p. 707-716.
Yarahmadi Bafghi, A.,  Mohebbi , M., Fatehi Marji, M.,  Gholamnejad, J., 2016. Rock mass structural data analysis using image processing techniques (Case study: Choghart iron ore mine northern slopes): Journal of Mining and Enviroment.
Scientific Quarterly Journal of Iranian Association of Engineering Geology
Volume 9, Number 3 & 4
March 2016
Pages 97-103

Files

History

  • Receive Date: 18 October 2016
  • Revise Date: 19 March 2017
  • Accept Date: 31 January 2018

Share

How to cite

Statistics