Modern data analysis technologies used for geomechanical monitoring. Review

Authors

  • O.G. Besimbayeva Karaganda Technical University
  • E.N. Khmyrova Karaganda Technical University
  • M.S. Tutanova Karaganda Technical University
  • N. Flindt Heidelberg University of Education
  • R.R. Sharafutdinov Karaganda Technical University

DOI:

https://doi.org/10.31643/2023/6445.23

Keywords:

The concept of the "Internet of Things", deformation monitoring, "Big Data", neural networks, analytical models, modeling of deformation processes.

Abstract

The paper considers the possibilities of modern technologies and software that make it possible to create continuity of geomechanical monitoring of man-made objects from shooting in automatic mode, robotic surveillance systems, transmitting information over the Internet to cloud storage, to performing stability calculations, 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 alternative to 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 method is 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 the cloud 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 deformations of the mountain range.

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Author Biographies

O.G. Besimbayeva, Karaganda Technical University

Сandidate of technical sciences, Karaganda Technical University named after A. S. Saginov, Nursultan Nazarbayev, 56, 100027, Karaganda, Kazakhstan.

E.N. Khmyrova, Karaganda Technical University

Сandidate of technical sciences, Karaganda Technical University named after A. S. Saginov, Nursultan Nazarbayev, 56, 100027, Karaganda, Kazakhstan.

M.S. Tutanova, Karaganda Technical University

Master of Science, A. S. Saginov Karaganda Technical University, Nursultan Nazarbayev, 56, 100027, Karaganda, Kazakhstan.

N. Flindt, Heidelberg University of Education

Doctor, Professor, Heidelberg University of Education, Keplerstraße 87, 69120 Heidelberg, Germany.

R.R. Sharafutdinov, Karaganda Technical University

Master of Engineering and Technology, Karaganda Technical University named after A. S. Saginov, 56, 100027, Karaganda, Kazakhstan.

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Published

2022-10-12

How to Cite

Besimbayeva, O., Khmyrova, E., Tutanova, M., Flindt, N., & Sharafutdinov, R. (2022). Modern data analysis technologies used for geomechanical monitoring. Review . Kompleksnoe Ispolzovanie Mineralnogo Syra = Complex Use of Mineral Resources, 326(3), 5–15. https://doi.org/10.31643/2023/6445.23

Issue

Section

Engineering and technology