The coal industry is a high risk, high difficulty industry, and the annual global mine accident rate is high, so the safety of coal mine underground operations has been a concern. With the development of technology, the application of intelligent security technology in coal mine safety has broad prospects. In this paper, the research progress of vital signs monitoring and support equipment for underground personnel in coal mines is reviewed. The two main methods to ensure the safety of miners are discussed. They consist of directly monitoring human vital signs through portable devices such as smart helmets and smartwatches and indirectly monitoring underground environmental parameters. In addition, the application of information technology, sensor technology and artificial intelligence in vital signs monitoring is briefly discussed, and some future research directions are proposed. For example, through big data and artificial intelligence technology, vital signs data can be compared with historical data, individual health trends and potential risks can be analyzed, and we can provide personalized health management programs for miners. These technologies not only improve the safety of underground coal mine operation, but also provide an important guarantee for the realization of intelligent and safe coal mine production.

Deuterium flux through the thin wall of a palladium tube has been studied by monitoring gas pressure and temperature. A high-precision calorimeter (Calvet) was used to detect heat flow when the heater was shut down and the palladium tube was cooling down slowly. At certain temperatures an abnormal deuterium flux appeared. This deuterium flux reached a peak when the temperature of the palladium was decreasing. This abnormal deuterium flux differs from the monotonic feature of a normal diffusive flux and is accompanied by a heat flow.

In this study, we develop a fully coupled thermal-hydrological-mechanical-chemical (THMC) model to analyze the spontaneous combustion process of underground coal seams, focusing on investigating the influences of the pressure difference between oxygen and coal, the rate of coal-oxygen reaction heat, and the activation energy. The simulation results show that as oxygen propagates into the coal seams, the coal-oxygen reaction causes the spontaneous combustion of coal to heat. The consumption of oxygen leads to an increase in oxygen consumption along the way and a decrease in gas pressure. The permeability near the right boundary increases while significantly reducing the area far away from the right boundary as the predominant effect of spontaneous combustion. Additionally, a sensitivity study shows that a more considerable pressure difference and coal-oxygen reaction heat contribute to promoting the coal temperature, while the activation energy has a slight effect. Moreover, an increase in coal-oxygen reaction heat and activation energy accelerates the oxygen consumption rate and thus causes a lower oxygen concentration. Overall, the results provide a basis for the prediction and prevention of coal seam spontaneous combustion.

To prevent and control the coal seam gas disaster affected by the reverse fault, we performed gas seepage tests, which consider stress-loading and unloading schemes, to investigate the stress change and coal permeability of the mining coal with reverse fault. The experimental results show that the mechanical behavior and permeability change of the mining coal are related to the distance between the coal and the reverse fault. The stress concentration coefficient of the coal body gradually increases. The closer is the distance between the coal and the reverse fault, the larger are the deviatoric stress peak and strain. In comparison with the coal sample M1 that is 5 m away from the reverse fault, the deviatoric stress peak and axial strain of the coal sample M3, 35 m away from the reverse fault, increase by 40.74% and 26.73%, respectively. In this stage, the permeability of M1, M2, and M3 coal samples increases by 22.1%, 28.0%, and 36.7%, respectively. In another stage, the stress concentration coefficient of coal increases to the peak and then decreases, causing the deviatoric stress peak and strain of coal to rise first and then fall. In comparison with the coal sample M4 that is 65 m away from the reverse fault, the deviatoric stress peak and axial strain of coal sample M6, 5 m away from the reverse fault, decrease by 29.48% and 5.55%, respectively. The permeability of coal samples M4, M5, and M6 increases by 23.6%, 37.2%, and 20.8%, respectively. Based on the gas seepage test results, we established the permeability model of mining-induced coal under the influence of a reverse fault, with consideration of the volume changes of coal fractures induced by adsorption and desorption. In the model, the variations of permeability in both stages of the prepeak and postpeak were deduced, which was verified with the experimental data. The verification results demonstrate that the proposed model has the capacity to predict the permeability evolution of mining coal under the influence of a reverse fault.