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PHYSICS OF ROCKS AND PROCESSES
ArticleName Integrated monitoring of engineering structures in mining
DOI 10.17580/em.2018.02.05
ArticleAuthor Cheskidov V. V., Lipina A. V., Melnichenko I. A.
ArticleAuthorData

National University of Science and Technology — MISIS, Moscow, Russia^

Cheskidov V. V., Associate Professor, vcheskidov@misis.ru
Lipina A. V., Assistant
Melnichenko I. A., Post-Graduate Student

Abstract

Technological development in mining calls for accurate modeling and continuous awareness of the behavior of engineering objects in order to ensure mine safety. The information technologies and Big Data enable the next-level design, operation and management in the mining industry. The principal tool of acquisition of information on the parameters and behavior of basic production systems under operation is monitoring. Modern mines are the complex nature-and-technology systems, and their control is impossible without full and reliable information on the behavior of the components. The most hazardous structures in open pit mining are slopes of pit walls, dumps and hydraulic fill dams. The slope stability is governed by a set of factors (geology, hydrogeology, technology and other) which feature high variability in space and time. The ground water level monitoring in a slope structure allows interactive assessment of the slope behavior through calculation of safety factor using geomechanical models of the slope. In the course of time, as a result of variation in operating conditions in the mining waste storage areas, or due to environmental changes (extra moistening of clay rocks, thawing of frozen soil, etc.), physical and mechanical properties of stock piles and their bottoms alter. This fact dictates periodic determination of basic characteristics of slopes: density, cohesion and internal friction angle; the latter, together with the landslide body geometry and hydrogeological conditions govern the ratio of shearing and retaining forces. The optimized-rate measurement of water levels in an aquifer and adjustment of physical and mechanical properties of rocks by means of testing or statistical checking enables reduction in total operating cost and ensures ecological and production safety. Thus, monitoring of engineering objects in mining is the most critical Big Data tool in practical mining upon transition to the technologies of the Fourth Industrial Revolution.

The study was supported by the Russian Foundation for Basic Research, Project No. 16-35-60116 mol_а_dk.

keywords Mineral mining, IT in mining, Big Data, monitoring, slope, information processing methods, neural networks
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