Air-quality measurements in a deep underground mine are a critical issue. The cost of ventilation, as well as the geometry of the considered mine, make this process very difficult, and local air quality may be a danger to miners. Thus, portable, personal devices are required to inform miners about gas hazards. There are available tools for that purpose; however, they do not allow the storage of data collected during a shift. Moreover, they do not allow the basic analysis of the acquired data cost-effectively. This paper aims to present a system using low-cost gas sensors and microcontrollers, and takes advantage of commonly used smartphones as a computing and visualization resource. Finally, we demonstrate monitoring system results from a test in an underground mine located in Poland.

Comparative strength analysis of two popular options of the radial centrifugal fan impeller design used in horizontal conveyor dryer for fine-grained raw materials is presented. Three types of materials for impeller manufacturing—ASTM A36 steel, Hardox 450 steel and aluminium alloy 6061-T6 are considered. The finite element method (FEM) has been used to investigate stresses and deformations of the impeller within the operational speed range. Analysis shows that the better design is the impeller made of Hardox 450 steel with a central disk. Although the maximum stress is slightly higher in the blades slot for central disk fitting for this design option, it has greatly reduced stresses in contact edges with two other disks (by 22–38%) and blades bending deformation (by 51%). For this design, the maximum operational rotation speed is 1135 min${}^{-1}$ according to the yield strength with a 15% safety factor, while for basic design, it is 1225 min${}^{-1}$. The rational choice of material depends on maximum value of the yield stress to density ratio as well as taking into account the operating conditions and required fan performance. Recommendations for manufacturing the centrifugal fan impeller related to chosen material are given.

The exploitation of natural resources is associated with many natural hazards. Currently, the copper ore deposits exploited in Polish mines are located at a depth of about 1200 m below the surface. The primary temperature of the rocks in the exploited areas reaches 48 ${}^{\circ }$C, which constitutes a major source of heat flux to the mine air. However, another important source of heat is the machine plant, which mainly consists of machines powered by diesel engines. Following the results of in situ measurements, boundary conditions for a simulation were determined and a geometric model of the cabin was created. Furthermore, an average human model was created, whose radiative heat transfer was included in the analysis. Three cases were studied: the first covering the current state of thermal conditions, based on the measurement results, and two cases of forecast conditions. In the second case, the temperature of the conditioned air was determined, and in the third, the flow velocity required to ensure thermal comfort was found. The results of the simulation indicated that for the microclimatic conditions established based on the measurements (ambient air temperature in the excavation 35.0 ${}^{\circ }$C, air-conditioned airflow 2.4 × 10${}^{-2}$ m${}^3$/s, and temperature 10.0 ${}^{\circ }$C), the temperature of the air inside the air-conditioned operator’s cabin would be 20.4 ${}^{\circ }$C. Based on the personal mean vote (PMV) index, it was concluded that the thermal sensation would range from neutral to slightly cool, which confirmed the legitimacy of the actions taken to reduce the adverse impact of the microclimatic conditions on workers in the workplace. However, for the case of predicted conditions of enhanced heat flux from strata and machinery, resulting in an average ambient temperature increased to 38.0 ${}^{\circ }$C, it would be necessary to lower the temperature of air from the air conditioner to 8.00 ${}^{\circ }$C or increase the flow rate to 3.14 × 10${}^{-2}$ m${}^3$/s to maintain thermal comfort at the same level of PMV index.

An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load–haul–dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used to establish a nonlinear relationship between input and output layers. The predicted values of NOx emissions have less than 15% error compared to the real values measured by the LHD onboard monitoring system by the standard sensor. This is considered quite good efficiency for dynamic behaviour prediction of extremely complex systems. The achieved accuracy of NOx prediction allows the application of the ANN-based “soft sensor” in environmental impact estimation and ventilation system demand planning, which depends on the number of working LHDs in the underground mine. The proposed solution to model NOx concentrations from mining machines will help to provide a better understanding of the atmosphere of the working environment and will also contribute to improving the safety of underground crews.

The underground mining industry is at the forefront when it comes to unsafe conditions at workplaces. As mining depths continue to increase and the mining fronts move away from the ventilation shafts, gas hazards are increasing. In this article, the authors developed a statistical polynomial model for nitrogen oxide (NOx) emission prediction of the LHD vehicle with a diesel engine. The best-achieved prediction accuracy by the 4th order polynomial model for 11 and 10 input variables is about 8% and 13%, respectively. It is comparable with the sensors’ accuracy of 10% at a stable regime of loading and 20% in the transient periods of operation. The obtained results allow planning of ventilation system capacity and power demand for the large fleet of vehicles in the deep underground mines.

Workstations in deep underground mines are among the most dangerous in the world. Workers are exposed to various hazards such as water hazards, climate hazards, and gas hazards. In this article, the authors proposed the most suitable method for measuring nitrogen oxides, such as nitric oxide(NO) and nitrogen dioxide (NO₂), under actual underground mine conditions. The selection of the method was based on a literature review, in which the authors presented a brief characterization of available measurement methods and proposed their classification into four categories: chemical methods, electrochemical methods, chemiluminescence methods, and analytical methods. A SWOT analysis was used to select the appropriate method for NOx determination. The authors focused on identifying the most universal method that can handle measurements in the harsh conditions of underground mines, with an emphasis on ease of use in the field. Due to the mine atmosphere being rich in harmful substances, the selectivity of the method was also taken into account. The method chosen by the authors is intended for measuring both low concentrations of NOx (in the atmosphere) and high concentrations (diesel exhaust emissions). Because of the versatility of the method and its potential application in both small and large laboratories, the cost criterion was also considered.