ABSTRACT
Atmospheric Monitoring Systems (AMS) used in underground coal mines typically collect and store a tremendous amount of data. Logged values, such as gas concentrations, ambient temperature, barometric pressure, humidity, air velocity, as well as a variety of fan related data are seldom integrated into a single system for analysis. Typically, the data are utilized in individual systems by operators in order to make decisions regarding the health and safety of the workforce as well as for managing ventilation systems more efficiently.
This research discusses different studies that investigate the dependence between gas con-centration measurements from underground mines and atmospheric data by means statistical measures of association. The objective is to identify and quantify techniques that provide meaningful correlations between potentially harmful gas concentrations and meteorological variables which will allow the development of a robust predictive model. Preliminary results from a case study in the eastern USA are presented.
