摘要：Method of seismic active zones control is one of approaches of prediction of dynamic mountain pressure manifestations, which is to identify and analyze formation dynamics of seismo acoustic active zones and predict impact hazard based on revealed patterns of changes in geoacoustic activity of rock massif. The key point of this control method is the zone allocation where a potentially dangerous rock destruction source is formed. In the article, we propose an automated method for damage zone identification, based on the preliminary exclusion of background radiation by nonparametric density estimation method, the seismo acoustic active zone allocation by means of probabilistic cluster analysis and damage zone parametrization by characteristic ellipsoid selection. These tasks are part of complex geomechanical monitoring system development and are solved by upgrading and subsequent integration into the interacted software of the considered seismo acoustic active zone monitoring method. Their solution will allow to fully automate predicting dangerous state process of the controlled rock mass, improving forecast quality and significantly reducing the time spent on obtaining final result.
其他摘要：Method of seismic active zones control is one of approaches of prediction of dynamic mountain pressure manifestations, which is to identify and analyze formation dynamics of seismo acoustic active zones and predict impact hazard based on revealed patterns of changes in geoacoustic activity of rock massif. The key point of this control method is the zone allocation where a potentially dangerous rock destruction source is formed. In the article, we propose an automated method for damage zone identification, based on the preliminary exclusion of background radiation by nonparametric density estimation method, the seismo acoustic active zone allocation by means of probabilistic cluster analysis and damage zone parametrization by characteristic ellipsoid selection. These tasks are part of complex geomechanical monitoring system development and are solved by upgrading and subsequent integration into the interacted software of the considered seismo acoustic active zone monitoring method. Their solution will allow to fully automate predicting dangerous state process of the controlled rock mass, improving forecast quality and significantly reducing the time spent on obtaining final result.
