Self-Excited Acoustical Measurement System for Rock Mass Stress Mapping

This paper presents the results of a preliminary study of a self-excited acoustical system (SAS) for nondestructive testing (NDT). The SAS system was used for mine excavation stresses examination. The principle of operation of the SAS system based on the elastoacoustical effect is presented. A numerical analysis of the excavation was carried out considering the stress factor. An equivalent model based on a two-degree-of-freedom system with a delay has been developed. This model allowed to determine the relation which relates the frequency of the self-excited system to the stress level in the studied ceiling section. This relationship is defined by the elastoacoustic coefficient. The test details for anchorages in laboratory conditions and Wieliczka Salt Mine were presented. This research details of a method for creating actual stress maps in the ceiling of a mine excavation. The results confirmed the possibility of using the new measurement system to monitor the state of stresses in the rock mass.

Machine Learning for Mineral Identification and Ore Estimation from Hyperspectral Imagery in Tin–Tungsten Deposits: Simulation under Indoor Conditions

This study aims to assess the feasibility of delineating and identifying mineral ores from hyperspectral images of tin–tungsten mine excavation faces using machine learning classification. We compiled a set of hand samples of minerals of interest from a tin–tungsten mine and analyzed two types of hyperspectral images: (1) images acquired with a laboratory set-up under close-to-optimal conditions, and (2) a scan of a simulated mine face using a field set-up, under conditions closer to those in the gallery. We have analyzed the following minerals: cassiterite (tin ore), wolframite (tungsten ore), chalcopyrite, malachite, muscovite, and quartz. Classification (Linear Discriminant Analysis, Singular Vector Machines and Random Forest) of laboratory spectra had a very high overall accuracy rate (98%), slightly lower if the 450–950 nm and 950–1650 nm ranges are considered independently, and much lower (74.5%) for simulated conventional RGB imagery. Classification accuracy for the simulation was lower than in the laboratory but still high (85%), likely a consequence of the lower spatial resolution. All three classification methods performed similarly in this case, with Random Forest producing results of slightly higher accuracy. The user’s accuracy for wolframite was 85%, but cassiterite was often confused with wolframite (user’s accuracy: 70%). A lumped ore category achieved 94.9% user’s accuracy. Our study confirms the suitability of hyperspectral imaging to record the spatial distribution of ore mineralization in progressing tungsten–tin mine faces.

Machine-Learning for Mineral Identification and Ore Estimation From Hyperspectral Imagery in Tin-Tungsten Deposits

This study aims to assess the feasibility of delineating and identifying mineral ores from hyperspectral images of tin-tungsten mine excavation faces using machine-learning classification. We compiled a set of hand samples of minerals of interest from a tin-tungsten mine and analyzed two types of hyperspectral images: 1) images acquired with a laboratory set-up under close-to-optimal conditions; and 2) scan of a simulated mine face using a field set-up, under conditions closer to those in the gallery. We have analyzed the following minerals: cassiterite (tin ore), wolframite (tungsten ore), chalcopyrite, malachite, muscovite, and quartz. Classification (Linear Discriminant Analysis, Singular Vector Machines and Random Forest) of laboratory spectra had a very high overall accuracy rate (98%), slightly lower if the 450 – 950 nm and 950 – 1780 nm ranges are considered independently, and much lower (74.5%) for simulated conventional RGB imagery. Classification accuracy for the simulation was lower than in the laboratory but still high (85%), likely a consequence of the lower spatial resolution. All three classification methods performed similarly in this case, with Random Forest producing results of slightly higher accuracy. The user’s accuracy for wolframite was 85%, but cassiterite was often confused with wolframite (user’s accuracy: 70%). A lumped ore category achieved 94.9% user’s accuracy. Our study confirms the suitability of hyperspectral imaging to record the spatial distribution of ore mineralization in progressing tungsten-tin mine faces.

The Miocene Lacustrine Chalk from Lignite Bełchatów Deposit (Poland)—Structural and Textural Character and SO2 Sorption Properties in the Fluid Combustion Conditions

The Miocene lacustrine chalk in the Bełchatów lignite deposit is one of the most important accompanying minerals. It is found in three lithological varieties: white, dark and silicified. It is selectively operated and stored on anthropogenic deposits, representing the mineral resource base. The article presents the results of research on lacustrine chalk from the Szczerców mine excavation and accumulated on the anthropogenic deposit (the Szczerców field external landfill) regarding the possibility of using SO2 sorbent in the fluid combustion technology. It has been shown that primarily the structural and textural parameters of the rock, and to a lesser extent, the CaCO3 content, are responsible for the high efficiency of SO2 sorption. It has been proven that in this type of technology, the presence of carbonised plant matter only seemingly lowers the quality parameters of the raw material. It has a significant impact on the sorption properties, effectively influencing the expansion of porosity and specific surface during thermal decomposition. The expansion of the surface is mainly based on the pores on the border of mesopores and macropores, i.e., pores considered to be sorptive towards SO2. These pores, because they are formed in a lower temperature range than the calcite thermal dissociation process and are connected together to form a system, act as diffusion channels of CO2 from inside and SO2 into the inside of the sorbent grains, intensifying the decarbonisation and SO2 sorption processes.

CALCULATION OF STRENGTH OF DESIGN OF A SHAFT VENTILATION WALL OF A NEW TYPE AND ITS SEPARATE ELEMENTS

Based on mathematical modeling, the design of the power frame of the mine ventilation wall was finalized. This device is designed to quickly and reliably isolate a mine excavation to control the normal distribution of air andflue gases in the event of a fire.