Multiple type discriminating mine fire sensors.
Edwards-JC; Franks-RA; Friel-GF; Lazzara-CP; Opferman-JJ
Trans Soc Min Metall Explor 2003 Dec; 314:166-171
Researchers determined that a selection of different types of fire sensors could be used to discriminate mine fires from nuisance emissions produced by diesel equipment. A neural network (NN) was developed for application to coal, wood, and conveyor belt fires in the presence of diesel emissions and was evaluated with the successful prediction of 22 out of 23 mine fires based on a fire probability determination. The optimum sensor selection for the NN was composed of a carbon monoxide sensor, two types of metal oxide semiconductor sensors, and an optical-path smoke sensor.
Underground-mining; Mine-fires; Diesel-emissions; Coal-mining; Safety-research; Sensors; Hazards
NIOSH Pittsburgh Research Laboratory, P.O. Box 18070, Pittsburgh, PA 15236
Transactions of the Society for Mining, Metallurgy, and Exploration