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.

To control the gas accumulation and spontaneous combustion in goafs of coal mines, many measures such as airflow volume at the working face, gas extraction, and nitrogen injection in goafs have been taken. However, the principles of these measures contradict when controlling two hazards simultaneously. It is necessary to understand how the flow field in goafs is influenced by these measures. In this study, a mathematical model of the flow field in a goaf behind a u-type mechanized working face is established using the theory of porous media. The flow field in a goaf with the risk of gas accidents and spontaneous combustion was analyzed for different controlling measures. Taking the Daxing coal mine in Liaoning Province as an example, the main parameters, such as airflow volume, gas extraction, and nitrogen injection, were optimized based on the simulation results. These results are of great significance for the coupled control of gas accumulation and spontaneous combustion in goafs of coal mines.