Application of Methods of Artificial Intelligence in Systems for Continuous Automatic Monitoring of Dust Concentration and Deposits in Mine Atmosphere

TL;DR

This paper presents a new AI-based system for real-time, continuous monitoring of dust concentration and environmental parameters in coal mines, enhancing safety and environmental management.

Contribution

It introduces a theoretical framework and test results for an AI-driven system that improves mine atmosphere monitoring within the Industry 4.0 paradigm.

Findings

System can measure dust, humidity, flow velocity, and particle dispersion.

Real-time monitoring enhances safety and environmental control.

AI-based approach improves accuracy and responsiveness.

Abstract

With the growth of coal production, the load on the production capacity of coal enterprises also increases, which leads to a concomitant increase in dust formation in both opencast and underground methods of mining coal deposits. Dust, generated during drilling, blasting operations, excavation, loading, crushing and transportation of mined rock is one of the factors that has a negative impact on the health of mining workers and on the level of environmental pollution with solid particles. Thus, increasing the efficiency of controlling the concentration of solid particles in the mine atmosphere and dust deposits is an urgent scientific and technical task. In doing so, the use of modern digital technologies within the framework of the industry 4.0 concept makes it possible to develop approaches that can significantly improve the quality of monitoring the state of the mine atmosphere at coal mining enterprises. This article provides a theoretical basis and test results for a system for continuous automatic monitoring of dust concentration in a mine atmosphere as the component of the multifunctional coal mine safety system. It is shown that monitoring the state of mine workings aerological safety can be carried out in real time through the system of the new generation using artificial intelligence. The ability of the proposed system to measure basic physical parameters affecting dust deposition (disperse composition, air humidity, dust concentration and air flow velocity) is noted.