Search

The roof and floor of a water-rich area can be explored using traditional two-dimensional (2D) electrical resistivity tomography (ERT), but this method cannot be applied to a water-rich internal working face. In this paper, the resistivity of an internal working face was determined using 2D ERT by laying electrodes and cables in two adjacent roadways and using an equatorial dipole device. The water inrush process of the goaf floor in the study area was monitored with pre-implanted electrodes and cables at the front of the mining working face and was analyzed using the processed results of four acquired data sets. The location of the water inrush from the floor was determined based on the change in the resistivity of the floor and the hydrological variations at the observational hole, which provided the basis for how to stop the water inrush. [ABSTRACT FROM AUTHOR]

A risk evaluation method based on principal component analysis, fuzzy mathematics, particle swarm optimization, and support vector classification, is proposed due to the limitations of the water inrush coefficient method. The many factors that influence coal floor water inrush were categorized as structural, hydrogeological, coal seam occurrence and mining condition principal components, according to principal component analysis, among which the structural and mining condition components were the most important. The principal component factors were then fuzzified. Finally, an evaluation method was established, with the parameters of the supporting vector classification optimized through the particle swarm algorithm. The validity of the method was demonstrated by comparing its predictions with actual conditions at ten coal seam mining faces. [ABSTRACT FROM AUTHOR]