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ArticleName The automated ore flow quality stabilization system in mining
DOI 10.17580/gzh.2015.12.16
ArticleAuthor Rylnikov A. G., Novikov A. N.

VIST Group, Moscow, Russia:
A. G. Rylnikov, Head of a School, Candidate of Engineering Sciences,


North Ural Gold, Krasnoturinsk, Russia:
A. N. Novikov, Chief Executive Officer


The application of the modern automated system to control the quality of ore fed to processing enables reduction in operating expenditures and improvement of marketable product quality. Technically, it is more feasible to control qualitative characteristics of ore flow in opencast mining by means of satellite navigation and information system as operating opencast mines already have installed basic blocks of such systems. The automated quality stabilization system for ore flows has been introduced in Vorontsovsky opencast gold mine of North Ural Gold Company. The idea of having the wanted ore quality rests upon formation of ore flows based on quality of ore from individual extraction block, predicted using permanently updated block model of ore deposit and supervising the processes of drilling, breakage and haulage of ore; the number of ore flows and ore blending regimes are governed by the characteristics and location of faces, as well as the number and volume of tipping points in an open pit mine. The article analyzes the prospects for automated ore flow quality control systems in underground mining. For the moment, separate elements of such systems have been trialed in underground mines. The difficulty is connected with the multi-stage formation of ore quality indexes, considering quality indexes of ore from separate extraction units (chambers, strips) and with the sequential merging of such flows via the system of ore passes into the common ore flow mine network.
The study was supported by the Russian Science Foundation, Grant No. 14-17-00050.

keywords Ore flow, ore quality, quality stabilization, automated control system, opencast mine, underground mine

1. Pytalev I. A., Rylnikov A. G. Informatsionnye sistemy upravleniya kachestvom rudopotokov na gornom predpriyatii (Information systems of ore flow quality control at mining enterprise). Under the editorship of D. R Kaplunov. Moscow : MediaMir, 2015. 188 p.
2. Trubetskoy K. N., Pytalev I. A., Rylnikov A. G. Avtomatizirovannye sistemy upravleniya kachestvom rudopotokov na karerakh (Automated systems of ore flow quality control at mines). Marksheyderskiy vestnik = Mine surveyor bulletin. 2013. No. 6. pp. 5–10.
3. Kozhiev Kh. Kh., Lomonosov G. G. Rudnichnye sistemy upravleniya kachestvom mineralnogo syrya (Mine systems of mineral quality control). Moscow : Mir gornoy knigi, 2008. 294 p.
4. Trubetskoy K. N., Kuleshov A. A., Klebanov A. F., Vladimirov D. Ya. Sovremennye sistemy upravleniya gornotransportnymi kompleksami (Modern systems of control of minetransport complexes). Under the editorship of K. N. Trubetskoy. Saint Petersburg : Nauka, 1977. 306 p.
5. Borbolin D. M., Rylnikov A. G., Pudov A. A., Novikov A. V., Volgina N. V. Vnedrenie sistemy dispetcherizatsii «Karer» na Vorontsovskom mestorozhdenii (Introduction of «Karer» dispatching system at Vorontsovskoe deposit). Gornyi Zhurnal = Mining Journal. 2011. No. 7. pp. 89–93.
6. Kaplunov D. R., Manilov I. A. Stabilizatsiya kachestva rudy pri podzemnoy dobyche (Stabilization of ore quality during the underground mining). Moscow : Nedra, 1983. 236 p.
7. Chadwick J., Boden H. Great Mines: Finland’s Kemi Chrome. International Mining. October 2015. pp. 8–12.
8. Moore P. Assignment autonomy. International Mining. 2015. pp. 14–24.
9. Thrybom L., Neander J., Hansen E., Landemas K. Future Challenges of Positioning in Underground Mines. IFAC-PapersOnLine. Elsevier Ltd., 2015. Vol. 48, Iss. 10. pp. 222–226.
10. Cai C., Luo X., Zhu J. Modified algorithm of combined GPS/GLONASS precise point positioning for applications in open-pit mines. Transactions of Nonferrous Metals Society of China. 2014. Vol. 24, No. 5. pp. 1547–1553.
11. Sun J., Li C. In-pit coal mine personnel uniqueness detection technology based on personnel positioning and face recognition. International Journal of Mining Science and Technology. 2013. Vol. 23, Iss. 3. pp. 357–361.
12. Hammer F., Pichler M., Fenzl H., Gebhard A., Hesch C. An acoustic position estimation prototype system for underground mining safety. Applied Acoustics. 2015. Vol. 92. pp. 61– 74.

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