Modern data analysis technologies used for geomechanical monitoring. Review
Besimbayeva O.G. Khmyrova E.N. Tutanova M.S. Flindt N. Sharafutdinov R.R.
12 October 2023Institute of Metallurgy and Ore Beneficiation JSC
Kompleksnoe Ispolzovanie Mineralnogo Syra
2023#326Issue 35 - 15 pp.
The paper considers the possibilities of modern technologies and software that make it possible to create continuity ofgeomechanical monitoring of man-made objects from shooting in automatic mode, robotic surveillance systems, transmitting information over the Internet to cloud storage, to performing stabilitycalculations, determining the parameters of displacement and deformation of slopes of ledges and sides of quarries. The development of modern technologies for collecting and processing information allows the use of artificial neural networks that are adapted for modeling geodetic deformations. Technogenic objects, which are very complex systems, have a huge number of external factors affecting the stability of the mountain range, so it becomes incredibly difficult to take into account and determine the amount of displacement and deformation. Due to the complexity and variety of influencing factors, it becomes necessary to use a new system for assessing the state of objects, called neural networks. The training of such a system is based on the already available research results collected during the direct operation of industrial enterprises. Neural networks can become an alternativeto various methods of describing deformation processes, especially in the continuous monitoring of man-made objects, where there is no a priori knowledge of the underlying deformation processes. For effective monitoring and forecasting of deformation processes at a mining enterprise, a multiparametric monitoring methodis needed, which includes a comprehensive system based on GPS measurements, supplemented with data from sensors for changes in water level and changes in stresses and deformations of the array. The results of automated survey and data recording sent to thecloud storage are distributed using Big Data technology and analyzed by geoinformation systems. In turn, the adaptation of neural networks to model deformations allows specialists to obtain a good alternative to the description of structural deformationsof the mountain range.
Big Data, neural networks , analytical models , deformation monitoring , modeling of deformation processes , neural networks , The concept of the Internet of Things
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Karaganda Technical University, Karaganda, Kazakhstan
Heidelberg University of Education, Heidelberg, Germany
Karaganda Technical University
Heidelberg University of Education
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026