Neural network-based experimental study on shaft water sealing by grouting

Shaft is the jaws of coal mines. Shaft water flood serious threatens the safety of the shaft. Water sealing by grouting (WSG) is one of the most effective ways to prevent and control shaft and underground-water flood for coal mine. In this paper, a scheme of water sealing by grouting (WSG) with organic material with high water content was designed for the alluvium strata grouting and the fracture strata grouting. By applying the basic principle of neural network (NN), a neural network-based system of grouting quantity prediction was set up. The intelligent prediction of grouting quantity was carried out. The NN predicted data and the data came from field observation were compared. The results show that the NN predicted grouting quantity is close to the real consumption of grouting quantity. And the consumption of the organic material with high water content (OMHWC) is reduced. The study has a certain realistic instructing meaning.