Рад у часопису

објављена верзија

енглески

Luka Crnogorac, Suzana Lutovac, Rade Tokalić, Miloš Gligorić, Zoran Gligorić

Steel Arch Support Deformations Forecast Model Based on Grey–Stochastic Simulation and Autoregressive Process

Applied Sciences

MDPI AG

2023

Relatively large deformations of the steel arch support in underground coal mines in the Republic of Serbia present one of the main problems for achieving the planned production of coal. Monitoring of the critical sections of the steel arch support in the underground roadways is necessary to gather quality data for the development of a forecasting model. With a new generation of 3D laser scanners that can be used in potentially explosive environments (ATEX), deformation monitoring is facilitated, while the process of collecting precise data is much shorter. In this paper, we used a combination of grey and stochastic system theory combined with an autoregressive process for processing collected data and the development of a forecasting model of the deformations of the steel arch support. Forecasted data accuracy based on the positions of the markers placed along the internal rim of support construction shows high accuracy with MAPE of 0.2143%. The proposed model can successfully be used by mining engineers in underground coal mines for steel arch support deformations prediction, consequentially optimizing the maintenance plan of the underground roadways and achieving planned production.

13

7

10.3390/app13074559

2076-3417

čelična podgrada; prognoza deformacija; vremenske serije; grey-stohastička simulacija; autoregresija; podzemni rudnik uglja

steel arch support; deformation forecast; time series; grey–stochastic simulation; autoregression; underground coal mining

https://www.mdpi.com/2076-3417/13/7/4559/pdf

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