Mine fire source discrimination using fire sensors and neural network analysis.
Edwards-JC; Friel-GF; Franks-RA; Lazzara-CP; Opferman-JJ
Combustion Fundamentals and Applications--Proceedings of the 2000 Technical Meeting of the Central States Section of the Combustion Institute, Indianapolis, Indiana. Pittsburgh, PA: The Combustion Institute, 2000 Apr; :207-211
Fire experiments were conducted in the Safety Research Coal Mine (SRCM) at the National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, with coal, diesel-fuel, electrical cable, conveyor-belt, and metal-cutting fire sources to determine the response of fire sensors to products-of- combustion (POC). Metal oxide semiconductor (MOS) and smoke fire sensors demonstrated an earlier fire detection capability than a carbon monoxide sensor. This capability was of particular significance for a conveyor-belt fire in which the optical visibility was reduced to 1.52 m with an increase in carbon monoxide of less than 2 ppm at a distance of 148 m from the fire. Application of a neural-network program to the sensor responses from each type of fire source resulted in correct classifications of coal, diesel-fuel, cable, belt, and metal-cutting combustion with a mean of 96% of the test data correctly classified.
Mining-industry; Underground-mining; Fire-safety; Fire-prevention; Monitors; Monitoring-systems
NIOSH, Pittsburgh Research Laboratory, P.O. Box 18070, Pittsburgh, PA 15236
Combustion Fundamentals and Applications Proceedings of the 2000 Technical Meeting of the Central States Section of the Combustion Institute