On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space

Study on the Distribution Law of Coal Seam Gas and Hydrogen Sulfide Affected by Abandoned Oil Wells

This paper is devoted to solving the problem of how to comprehensively control coal seam gas and hydrogen sulfide in the mining face, distributed from the coal seam in abandoned oil wells in coal mining resource areas. The abandoned oil wells of Ma tan 30 and Ma tan 31 in the No. I0104105 working face of the Shuang Ma Coal Mine were taken as examples. Through parameter testing, gas composition analysis, field investigation at the source distribution, and the influence range of gas and hydrogen sulfide in coal seam in the affected range of the abandoned oil wells were studied. The results show that the coal-bearing strata in Shuang Ma coal field belong to the coal–oil coexistence strata, and the emission of H2S gas in the local area of the working face is mainly affected by closed and abandoned oil wells. Within the influence range of the abandoned oil wells, along the direction of the working face, the concentration of CH4 and H2S gas in the borehole increases as you move closer to the coal center, and the two sides of the oil well show a decreasing trend. In the affected area of the abandoned oil well, the distribution of the desorption gas content in coal seam along the center distance of the oil well presents a decreasing trend in power function, particularly the closer the working face is to the center of the oil well. The higher the concentration of CH4 and H2S, the lower the concentration when the working face moves further away from the oil well. The influence radius of CH4 and H2S gas on the coal seam in the affected area of Ma tan 31 abandoned oil well is over 300 m. The results provide a theoretical basis for further understanding the law of gas and hydrogen sulfide enrichment in the mining face and the design of treatment measures within the influence range of abandoned oil wells.

Efficient Graphical Algorithm of Sensor Distribution and Air Volume Reconstruction for a Smart Mine Ventilation Network

The accurate and reliable monitoring of ventilation parameters is key to intelligent ventilation systems. In order to realize the visualization of airflow, it is essential to solve the airflow reconstruction problem using few sensors. In this study, a new concept called independent cut set that depends on the structure of the underlying graph is presented to determine the minimum number and location of sensors. We evaluated its effectiveness in a coal mine owned by Jinmei Corporation Limited (Jinmei Co., Ltd., Shanghai, China). Our results indicated that fewer than 30% of tunnels needed to have wind speed sensors set up to reconstruct the well-posed airflow of all the tunnels (>200 in some mines). The results showed that the algorithm was feasible. The reconstructed air volume of the ventilation network using this algorithm was the same as the actual air volume. The algorithm provides theoretical support for flow reconstruction.